Scholars@Duke
Nan Liu

Nan Liu

Adjunct Associate Professor in Biostatistics & Bioinformatics
Biostatistics & Bioinformatics, Division of Translational Biomedical

Selected Publications

SpNeigh: spatial neighborhood and differential expression analysis for high-resolution spatial transcriptomics.

Journal Article NAR Genom Bioinform · June 2026 Spatial transcriptomics technologies such as Xenium, MERFISH, and Visium HD enable high-resolution profiling of gene expression while preserving tissue architecture. However, most computational methods for spatial analysis do not explicitly model local tis ... Full text Link to item Cite

Barriers and opportunities of scaling ambient AI scribes for clinical documentation across diverse healthcare settings.

Journal Article NPJ Digit Med · March 23, 2026 Ambient AI scribes are reshaping clinical documentation and clinician-patient interactions. These tools were initially tested in low-acuity ambulatory settings. However, their deployment in diverse care settings raises new challenges. This perspective exam ... Full text Link to item Cite

Innovating global regulatory frameworks for generative AI in medical devices is an urgent priority.

Journal Article NPJ Digit Med · March 19, 2026 The integration of generative AI (GenAI) and large language models (LLMs) in healthcare presents both unprecedented opportunities and challenges, necessitating innovative regulatory approaches. In this perspective, we discuss the risks of GenAI and LLM-bas ... Full text Link to item Cite

HealthContradict: Evaluating biomedical knowledge conflicts in language models.

Journal Article NPJ Digit Med · January 21, 2026 How do language models use contextual information to answer health questions? How are their responses impacted by conflicting contexts? We assess the ability of language models to reason over long, conflicting biomedical contexts using HealthContradict, an ... Full text Link to item Cite

Large language models in global health

Journal Article Nature Health · January 15, 2026 Full text Cite

Real-world deployment and evaluation of PEri-operative AI CHatbot (PEACH): a large language model chatbot for peri-operative medicine.

Journal Article Anaesthesia · January 2026 INTRODUCTION: Large Language Models are emerging as powerful tools in healthcare, particularly for complex, domain-specific tasks. This study describes the development and evaluation of PEri-operative AI CHatbot (PEACH). It was developed by embedding 35 in ... Full text Link to item Cite

Enhancing Team Science by Training Collaborative Biostatisticians to have a Strong Statistical Voice.

Journal Article J Stat Theory Pract · 2026 Strong statistical voice is defined as the ability to advocate and negotiate for good and ethical statistical practices, including integrating and resolving differing scientific approaches. This skill is crucial for biostatisticians who work on biomedical ... Full text Link to item Cite

Reasoning-driven large language models in medicine: opportunities, challenges, and the road ahead.

Journal Article Lancet Digit Health · January 2026 Developments in large language models (LLMs) in the past 2 years have shifted the focus from text, image, and audio generation to LLMs capable of multistep reasoning (thinking). The development of LLMs is particularly important for medicine and health care ... Full text Link to item Cite

The evolving landscape of large language models and non-large language models in health care.

Journal Article Npj Health Syst · 2026 We analyzed 19,123 natural language processing-related studies to explore the differences in task distributions and application contexts between large language models (LLMs) and non-LLM methods in health care. Through topic modeling analysis, we found that ... Full text Link to item Cite

Survival Modeling Using Deep Learning, Machine Learning, and Statistical Methods: A Comparative Analysis for Predicting Mortality After Hospital Admission.

Journal Article Health Data Sci · 2026 Background: Survival analysis is essential for studying time-to-event outcomes and providing a dynamic understanding of the probability of an event occurring over time. Various survival analysis techniques, from traditional statistical models to state-of-t ... Full text Link to item Cite

Benchmarking Foundation Models with Multimodal Public Electronic Health Records.

Journal Article IEEE J Biomed Health Inform · December 16, 2025 Foundation models have emerged as a powerful approach for processing electronic health records (EHRs), offering flexibility to handle diverse medical data modalities. In this study, we present a comprehensive benchmark that evaluates the performance, fairn ... Full text Link to item Cite

Retrieval-augmented generation for generative artificial intelligence in health care

Journal Article Npj Health Systems · December 1, 2025 Generative artificial intelligence has brought disruptive innovations in health care but faces certain challenges. Retrieval-augmented generation (RAG) enables models to generate more reliable content by leveraging the retrieval of external knowledge. In t ... Full text Cite

FairFML: fair federated machine learning with a case study on reducing gender disparities in cardiac arrest outcome prediction

Journal Article Npj Health Systems · December 1, 2025 Health equity is a critical concern in clinical research and practice, as biased predictive models can exacerbate disparities in clinical decision-making and patient outcomes. As healthcare systems increasingly rely on data-driven models, ensuring fairness ... Full text Cite

Leveraging AI and transfer learning to enhance out-of-hospital cardiac arrest outcome prediction in diverse setting.

Journal Article NPJ Digit Med · November 21, 2025 Access to trustworthy artificial intelligence (AI) for clinical applications is uneven, especially in low-resource settings with limited and inconsistent data. Models from high-resource settings often fail to generalize. Transfer learning (TL) can adapt es ... Full text Link to item Cite

Enabling inclusive systematic reviews: incorporating preprint articles with large language model-driven evaluations.

Journal Article J Am Med Inform Assoc · November 1, 2025 OBJECTIVES: Systematic reviews in comparative effectiveness research require timely evidence synthesis. With the rapid advancement of medical research, preprint articles play an increasingly important role in accelerating knowledge dissemination. However, ... Full text Link to item Cite

Large language model as clinical decision support system augments medication safety in 16 clinical specialties.

Journal Article Cell Rep Med · October 21, 2025 Large language models (LLMs) have emerged as tools to support healthcare delivery, from automating tasks to aiding clinical decision-making. This study evaluated LLMs as alternative to rule-based alert systems, focusing on their ability to identify prescri ... Full text Link to item Cite

Reporting guideline for chatbot health advice studies: The CHART statement.

Journal Article Artif Intell Med · October 2025 The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and p ... Full text Link to item Cite

Developing federated time-to-event scores using heterogeneous real-world survival data.

Journal Article Comput Biol Med · October 2025 OBJECTIVE: Survival analysis serves as a fundamental component in numerous healthcare applications, where the determination of the time to specific events (such as the onset of a certain disease or death) for patients is crucial for clinical decision-makin ... Full text Link to item Cite

How can artificial intelligence transform the training of medical students and physicians?

Journal Article Lancet Digit Health · October 2025 Advances in artificial intelligence (AI), particularly generative AI, hold promise for transforming medical education and physician training in response to increasing health-care demands and shortages in the global health-care workforce. Meanwhile, challen ... Full text Link to item Cite

Reporting Guideline for Chatbot Health Advice Studies: Chatbot Assessment Reporting Tool (CHART) Statement.

Journal Article Ann Fam Med · September 22, 2025 The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of chatbots driven by generative artificial intelligence when summarizing clinical evidence and pro ... Full text Link to item Cite

Large Language Models in Randomized Controlled Trials Design: Observational Study.

Journal Article J Med Internet Res · September 3, 2025 BACKGROUND: Randomized controlled trials (RCTs) face challenges such as limited generalizability, insufficient recruitment diversity, and high failure rates, often due to restrictive eligibility criteria and inefficient patient selection. Large language mo ... Full text Link to item Cite

Development and evaluation of a lightweight large language model chatbot for medication enquiry.

Journal Article PLOS Digit Health · September 2025 Large Language Models (LLMs) show promise in augmenting digital health applications. However, development and scaling of large models face computational constraints, data security concerns and limitations of internet accessibility in some regions. We devel ... Full text Link to item Cite

FairFML: A Unified Approach to Algorithmic Fair Federated Learning with Applications to Reducing Gender Disparities in Cardiac Arrest Outcomes.

Journal Article Stud Health Technol Inform · August 7, 2025 Addressing algorithmic bias in healthcare is crucial for ensuring equity in patient outcomes, particularly in cross-institutional collaborations where privacy constraints often limit data sharing. Federated learning (FL) offers a solution by enabling insti ... Full text Link to item Cite

Transfer Learning Enhances Neurological Outcome Prediction for Out-of-Hospital Cardiac Arrest: Validation Across Diverse Geographic Contexts.

Journal Article Stud Health Technol Inform · August 7, 2025 Developing accurate risk stratification models for out-of-hospital cardiac arrest (OHCA) in low-resource settings is challenging due to small sample sizes and poor data quality. The Pan-Asian Resuscitation Outcomes Study (PAROS) network provides a valuable ... Full text Link to item Cite

Reporting guideline for Chatbot Health Advice studies: the CHART statement.

Journal Article BMC Med · August 1, 2025 BACKGROUND: The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical ev ... Full text Link to item Cite

Reporting Guideline for Chatbot Health Advice Studies: The CHART Statement.

Journal Article JAMA Netw Open · August 1, 2025 IMPORTANCE: The rise in chatbot health advice (CHA) studies is accompanied by heterogeneity in reporting standards, impacting their interpretability. OBJECTIVE: To provide reporting recommendations for studies evaluating the performance of generative artif ... Full text Link to item Cite

Reporting guideline for chatbot health advice studies: the Chatbot Assessment Reporting Tool (CHART) statement.

Journal Article Br J Surg · August 1, 2025 The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and p ... Full text Link to item Cite

Reporting guidelines for chatbot health advice studies: explanation and elaboration for the Chatbot Assessment Reporting Tool (CHART).

Journal Article BMJ · August 1, 2025 The Chatbot Assessment Reporting Tool (CHART) reporting guideline promotes transparent and comprehensive reporting of studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots for the purposes of summarising clinical evi ... Full text Link to item Cite

Clinical and economic impact of a large language model in perioperative medicine: a randomized crossover trial.

Journal Article NPJ Digit Med · July 21, 2025 Preoperative assessment is a critical but time-consuming component of perioperative care, often hindered by poor guideline adherence and high documentation burdens. This study evaluates the impact of PEACH (PErioperative AI CHatbot), an LLM-based clinical ... Full text Link to item Cite

Insights Into the Current and Future State of AI Adoption Within Health Systems in Southeast Asia: Cross-Sectional Qualitative Study.

Journal Article J Med Internet Res · June 16, 2025 BACKGROUND: Artificial intelligence (AI) holds potential to enhance health systems worldwide. However, its implementation in health systems in Southeast Asia (SEA)-a region of diverse geopolitical and socioeconomic development-has been understudied. OBJECT ... Full text Link to item Cite

A scoping review and evidence gap analysis of clinical AI fairness.

Journal Article NPJ Digit Med · June 14, 2025 The ethical integration of artificial intelligence (AI) in healthcare necessitates addressing fairness. AI fairness involves mitigating biases in AI and leveraging AI to promote equity. Despite advancements, significant disconnects persist between technica ... Full text Link to item Cite

⁠Advancing ethical AI in healthcare through interpretability.

Journal Article Patterns (N Y) · June 13, 2025 Interpretability is essential for building trust in health artificial intelligence (AI), but ensuring trustworthiness requires addressing broader ethical concerns, such as fairness, privacy, and reliability. This opinion article discusses the multilayered ... Full text Link to item Cite

The Use of Large Language Models and Their Association With Enhanced Impact in Biomedical Research and Beyond

Journal Article Medcomm Future Medicine · June 1, 2025 The release of ChatGPT in 2022 has catalyzed the adoption of large language models (LLMs) across diverse writing domains, including academic writing. However, this technological shift has raised critical questions regarding the prevalence of LLM usage in a ... Full text Cite

FedIMPUTE: Privacy-preserving missing value imputation for multi-site heterogeneous electronic health records.

Journal Article J Biomed Inform · May 2025 OBJECTIVES: We propose FedIMPUTE, a communication-efficient federated learning (FL) based approach for missing value imputation (MVI). Our method enables multiple sites to collaboratively perform MVI in a privacy-preserving manner, addressing challenges of ... Full text Link to item Cite

Retrieval augmented generation for 10 large language models and its generalizability in assessing medical fitness.

Journal Article NPJ Digit Med · April 5, 2025 Large Language Models (LLMs) hold promise for medical applications but often lack domain-specific expertise. Retrieval Augmented Generation (RAG) enables customization by integrating specialized knowledge. This study assessed the accuracy, consistency, and ... Full text Link to item Cite

A scoping review on generative AI and large language models in mitigating medication related harm.

Journal Article NPJ Digit Med · March 28, 2025 Medication-related harm has a significant impact on global healthcare costs and patient outcomes. Generative artificial intelligence (GenAI) and large language models (LLM) have emerged as a promising tool in mitigating risks of medication-related harm. Th ... Full text Link to item Cite

Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis.

Journal Article JMIR AI · March 27, 2025 BACKGROUND: A major challenge in using electronic health records (EHR) is the inconsistency of patient follow-up, resulting in right-censored outcomes. This becomes particularly problematic in long-horizon event predictions, such as autism and attention-de ... Full text Link to item Cite

PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods.

Journal Article BMJ · March 24, 2025 The Prediction model Risk Of Bias ASsessment Tool (PROBAST) is used to assess the quality, risk of bias, and applicability of prediction models or algorithms and of prediction model/algorithm studies. Since PROBAST’s introduction in 2019, much progress has ... Full text Link to item Cite

Causal inference from observational data in neurosurgical studies: a mini-review and tutorial.

Journal Article Acta Neurochir (Wien) · February 12, 2025 BACKGROUND: Establishing a causation relationship between treatments and patient outcomes is of essential importance for researchers to guide clinical decision-making with rigorous scientific evidence. Despite the fact that randomized controlled trials are ... Full text Link to item Cite

Reverse Time-to-Death as Time-Scale in Time-to-Event Analysis for Studies of Advanced Illness and Palliative Care.

Journal Article Stat Med · February 10, 2025 Incidence of adverse outcome events rises as patients with advanced illness approach end-of-life. Exposures that tend to occur near end-of-life, for example, use of wheelchair, oxygen therapy and palliative care, may therefore be found associated with the ... Full text Link to item Cite

Artificial intelligence in obstetric anaesthesiology - the future of patient care?

Journal Article Int J Obstet Anesth · February 2025 The use of artificial intelligence (AI) in obstetric anaesthesiology shows great potential in enhancing our practice and delivery of care. In this narrative review, we summarise the current applications of AI in four key areas of obstetric anaesthesiology ... Full text Link to item Cite

Assessing Risk in Implementing New Artificial Intelligence Triage Tools-How Much Risk is Reasonable in an Already Risky World?

Journal Article Asian Bioeth Rev · January 2025 Risk prediction in emergency medicine (EM) holds unique challenges due to issues surrounding urgency, blurry research-practise distinctions, and the high-pressure environment in emergency departments (ED). Artificial intelligence (AI) risk prediction tools ... Full text Link to item Cite

Reporting guideline for chatbot health advice studies: the Chatbot Assessment Reporting Tool (CHART) statement.

Journal Article BMJ Med · 2025 The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarising clinical evidence and p ... Full text Link to item Cite

Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Structured Data Analysis.

Journal Article Health Data Sci · 2025 Background: Clinical and biomedical research in low-resource settings often faces substantial challenges due to the need for high-quality data with sufficient sample sizes to construct effective models. These constraints hinder robust model training and pr ... Full text Link to item Cite

A modified and weighted Gower distance-based clustering analysis for mixed type data: a simulation and empirical analyses.

Journal Article BMC Med Res Methodol · December 18, 2024 BACKGROUND: Traditional clustering techniques are typically restricted to either continuous or categorical variables. However, most real-world clinical data are mixed type. This study aims to introduce a clustering technique specifically designed for datas ... Full text Link to item Cite

Leveraging anatomical constraints with uncertainty for pneumothorax segmentation.

Journal Article Health Care Sci · December 2024 BACKGROUND: Pneumothorax is a medical emergency caused by the abnormal accumulation of air in the pleural space-the potential space between the lungs and chest wall. On 2D chest radiographs, pneumothorax occurs within the thoracic cavity and outside of the ... Full text Link to item Cite

Mitigating Cognitive Biases in Clinical Decision-Making Through Multi-Agent Conversations Using Large Language Models: Simulation Study.

Journal Article J Med Internet Res · November 19, 2024 BACKGROUND: Cognitive biases in clinical decision-making significantly contribute to errors in diagnosis and suboptimal patient outcomes. Addressing these biases presents a formidable challenge in the medical field. OBJECTIVE: This study aimed to explore t ... Full text Link to item Cite

Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist.

Journal Article Lancet Digit Health · November 2024 The widespread use of Chat Generative Pre-trained Transformer (known as ChatGPT) and other emerging technology that is powered by generative artificial intelligence (GenAI) has drawn attention to the potential ethical issues they can cause, especially in h ... Full text Link to item Cite

FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcare.

Journal Article Patterns (N Y) · October 11, 2024 The escalating integration of machine learning in high-stakes fields such as healthcare raises substantial concerns about model fairness. We propose an interpretable framework, fairness-aware interpretable modeling (FAIM), to improve model fairness without ... Full text Link to item Cite

Ascle-A Python Natural Language Processing Toolkit for Medical Text Generation: Development and Evaluation Study.

Journal Article J Med Internet Res · October 3, 2024 BACKGROUND: Medical texts present significant domain-specific challenges, and manually curating these texts is a time-consuming and labor-intensive process. To address this, natural language processing (NLP) algorithms have been developed to automate text ... Full text Link to item Cite

Disparities in clinical studies of AI enabled applications from a global perspective.

Journal Article NPJ Digit Med · August 10, 2024 Artificial intelligence (AI) has been extensively researched in medicine, but its practical application remains limited. Meanwhile, there are various disparities in existing AI-enabled clinical studies, which pose a challenge to global health equity. In th ... Full text Link to item Cite

Clinical domain knowledge-derived template improves post hoc AI explanations in pneumothorax classification.

Journal Article J Biomed Inform · August 2024 OBJECTIVE: Pneumothorax is an acute thoracic disease caused by abnormal air collection between the lungs and chest wall. Recently, artificial intelligence (AI), especially deep learning (DL), has been increasingly employed for automating the diagnostic pro ... Full text Link to item Cite

Variable importance analysis with interpretable machine learning for fair risk prediction.

Journal Article PLOS Digit Health · July 2024 Machine learning (ML) methods are increasingly used to assess variable importance, but such black box models lack stability when limited in sample sizes, and do not formally indicate non-important factors. The Shapley variable importance cloud (ShapleyVIC) ... Full text Link to item Cite

Medical Ethics of Large Language Models in Medicine

Journal Article NEJM AI · June 27, 2024 Full text Cite

Ethical and regulatory challenges of large language models in medicine.

Journal Article Lancet Digit Health · June 2024 With the rapid growth of interest in and use of large language models (LLMs) across various industries, we are facing some crucial and profound ethical concerns, especially in the medical field. The unique technical architecture and purported emergent abil ... Full text Link to item Cite

A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development.

Journal Article Environ Res · June 1, 2024 BACKGROUND: Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk factors studied. Our study adopted a machine learning approach to explore the role of the exposome starting ... Full text Link to item Cite

Towards proactive palliative care in oncology: developing an explainable EHR-based machine learning model for mortality risk prediction.

Journal Article BMC Palliat Care · May 20, 2024 BACKGROUND: Ex-ante identification of the last year in life facilitates a proactive palliative approach. Machine learning models trained on electronic health records (EHR) demonstrate promising performance in cancer prognostication. However, gaps in litera ... Full text Link to item Cite

Comparing Open-Access Database and Traditional Intensive Care Studies Using Machine Learning: Bibliometric Analysis Study.

Journal Article J Med Internet Res · April 17, 2024 BACKGROUND: Intensive care research has predominantly relied on conventional methods like randomized controlled trials. However, the increasing popularity of open-access, free databases in the past decade has opened new avenues for research, offering fresh ... Full text Link to item Cite

Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture.

Journal Article Cell Rep Med · February 20, 2024 Federated learning (FL) is a distributed machine learning framework that is gaining traction in view of increasing health data privacy protection needs. By conducting a systematic review of FL applications in healthcare, we identify relevant articles in sc ... Full text Link to item Cite

Federated Learning in Healthcare: A Benchmark Comparison of Engineering and Statistical Approaches for Structured Data Analysis.

Journal Article Health Data Sci · 2024 Background: Federated learning (FL) holds promise for safeguarding data privacy in healthcare collaborations. While the term "FL" was originally coined by the engineering community, the statistical field has also developed privacy-preserving algorithms, th ... Full text Link to item Cite

Transdisciplinary perspectives for health systems science.

Journal Article Npj Health Syst · 2024 Health systems science uses systems thinking as part of a transdisciplinary approach that transcends traditional disciplinary boundaries. It integrates and synthesizes knowledge from multiple disciplines to address real-world problems in healthcare with pr ... Full text Link to item Cite

Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation.

Journal Article Asia Pac J Ophthalmol (Phila) · 2024 PURPOSE: To describe choroidal thickness measurements using a sequential deep learning segmentation in adults who received childhood atropine treatment for myopia control. DESIGN: Prospective, observational study. METHODS: Choroidal thickness was measured ... Full text Link to item Cite

Topical Atropine for Childhood Myopia Control: The Atropine Treatment Long-Term Assessment Study.

Journal Article JAMA Ophthalmol · January 1, 2024 IMPORTANCE: Clinical trial results of topical atropine eye drops for childhood myopia control have shown inconsistent outcomes across short-term studies, with little long-term safety or other outcomes reported. OBJECTIVE: To report the long-term safety and ... Full text Link to item Cite

Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.

Journal Article J Am Med Inform Assoc · November 17, 2023 OBJECTIVES: Federated learning (FL) has gained popularity in clinical research in recent years to facilitate privacy-preserving collaboration. Structured data, one of the most prevalent forms of clinical data, has experienced significant growth in volume c ... Full text Link to item Cite

FedScore: A privacy-preserving framework for federated scoring system development.

Journal Article J Biomed Inform · October 2023 OBJECTIVE: We propose FedScore, a privacy-preserving federated learning framework for scoring system generation across multiple sites to facilitate cross-institutional collaborations. MATERIALS AND METHODS: The FedScore framework includes five modules: fed ... Full text Link to item Cite

Association between the extension of smoke-free legislation and incident acute myocardial infarctions in Singapore from 2010 to 2019: an interrupted time-series analysis.

Journal Article BMJ Glob Health · October 2023 BACKGROUND: We examined the association between smoke-free laws implemented in the outdoors and the common areas of residential apartment blocks and reported acute myocardial infarctions (AMI) in Singapore. METHODS: We used an interrupted time-series desig ... Full text Link to item Cite

Febrile infants risk score at triage (FIRST) for the early identification of serious bacterial infections.

Journal Article Sci Rep · September 22, 2023 We aimed to derive the Febrile Infants Risk Score at Triage (FIRST) to quantify risk for serious bacterial infections (SBIs), defined as bacteremia, meningitis and urinary tract infections. We performed a prospective observational study on febrile infants  ... Full text Link to item Cite

A translational perspective towards clinical AI fairness.

Journal Article NPJ Digit Med · September 14, 2023 Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the fairness of such data-driven insights remains a concern in high-stakes fields. Despite extensive developments, issues of AI fairness in clinical contexts have ... Full text Link to item Cite

Explainable artificial intelligence in ophthalmology.

Journal Article Curr Opin Ophthalmol · September 1, 2023 PURPOSE OF REVIEW: Despite the growing scope of artificial intelligence (AI) and deep learning (DL) applications in the field of ophthalmology, most have yet to reach clinical adoption. Beyond model performance metrics, there has been an increasing emphasi ... Full text Link to item Cite

AI and machine learning in resuscitation: Ongoing research, new concepts, and key challenges.

Journal Article Resusc Plus · September 2023 AIM: Artificial intelligence (AI) and machine learning (ML) are important areas of computer science that have recently attracted attention for their application to medicine. However, as techniques continue to advance and become more complex, it is increasi ... Full text Link to item Cite

A scoping review of the clinical application of machine learning in data-driven population segmentation analysis.

Journal Article J Am Med Inform Assoc · August 18, 2023 OBJECTIVE: Data-driven population segmentation is commonly used in clinical settings to separate the heterogeneous population into multiple relatively homogenous groups with similar healthcare features. In recent years, machine learning (ML) based segmenta ... Full text Link to item Cite

Application of a deep learning algorithm in the detection of hip fractures.

Journal Article iScience · August 18, 2023 This paper describes the development of a deep learning model for prediction of hip fractures on pelvic radiographs (X-rays). Developed using over 40,000 pelvic radiographs from a single institution, the model demonstrated high sensitivity and specificity ... Full text Link to item Cite

Artificial intelligence and machine learning in prehospital emergency care: A scoping review.

Journal Article iScience · August 18, 2023 Our scoping review provides a comprehensive analysis of the landscape of artificial intelligence (AI) applications in prehospital emergency care (PEC). It contributes to the field by highlighting the most studied AI applications and identifying the most co ... Full text Link to item Cite

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques.

Journal Article Artif Intell Med · August 2023 OBJECTIVE: The proper handling of missing values is critical to delivering reliable estimates and decisions, especially in high-stakes fields such as clinical research. In response to the increasing diversity and complexity of data, many researchers have d ... Full text Link to item Cite

Epicasting: An Ensemble Wavelet Neural Network for forecasting epidemics.

Journal Article Neural Netw · August 2023 Infectious diseases remain among the top contributors to human illness and death worldwide, among which many diseases produce epidemic waves of infection. The lack of specific drugs and ready-to-use vaccines to prevent most of these epidemics worsens the s ... Full text Link to item Cite

Large language models in health care: Development, applications, and challenges.

Journal Article Health Care Sci · August 2023 Recently, the emergence of ChatGPT, an artificial intelligence chatbot developed by OpenAI, has attracted significant attention due to its exceptional language comprehension and content generation capabilities, highlighting the immense potential of large l ... Full text Link to item Cite

Implementation of Prediction Models in the Emergency Department from an Implementation Science Perspective-Determinants, Outcomes, and Real-World Impact: A Scoping Review.

Journal Article Ann Emerg Med · July 2023 STUDY OBJECTIVE: Prediction models offer a promising form of clinical decision support in the complex and fast-paced environment of the emergency department (ED). Despite significant advancements in model development and validation, implementation of such ... Full text Link to item Cite

A universal AutoScore framework to develop interpretable scoring systems for predicting common types of clinical outcomes.

Journal Article STAR Protoc · June 16, 2023 The AutoScore framework can automatically generate data-driven clinical scores in various clinical applications. Here, we present a protocol for developing clinical scoring systems for binary, survival, and ordinal outcomes using the open-source AutoScore ... Full text Link to item Cite

Identifying clinical features and blood biomarkers associated with mild cognitive impairment in Parkinson disease using machine learning.

Journal Article Eur J Neurol · June 2023 BACKGROUND AND PURPOSE: A broad list of variables associated with mild cognitive impairment (MCI) in Parkinson disease (PD) have been investigated separately. However, there is as yet no study including all of them to assess variable importance. Shapley va ... Full text Link to item Cite

HRnV-Calc: A Software for Heart Rate n-Variability and Heart Rate Variability Analysis

Journal Article Journal of Open Source Software · May 31, 2023 Full text Cite

Did lockdown influence bystanders' willingness to perform cardiopulmonary resuscitation? A worldwide registry-based perspective.

Journal Article Resuscitation · May 2023 AIM: Bystander cardiopulmonary resuscitation (CPR) significantly increases the survival rate after out-of-hospital cardiac arrest. Using population-based registries, we investigated the impact of lockdown due to Covid-19 on the provision of bystander CPR, ... Full text Link to item Cite

Development and Asian-wide validation of the Grade for Interpretable Field Triage (GIFT) for predicting mortality in pre-hospital patients using the Pan-Asian Trauma Outcomes Study (PATOS).

Journal Article Lancet Reg Health West Pac · May 2023 BACKGROUND: Field triage is critical in injury patients as the appropriate transport of patients to trauma centers is directly associated with clinical outcomes. Several prehospital triage scores have been developed in Western and European cohorts; however ... Full text Link to item Cite

Evaluation of Machine Learning Methods Developed for Prediction of Diabetes Complications: A Systematic Review.

Journal Article J Diabetes Sci Technol · March 2023 BACKGROUND: With the rising prevalence of diabetes, machine learning (ML) models have been increasingly used for prediction of diabetes and its complications, due to their ability to handle large complex data sets. This study aims to evaluate the quality a ... Full text Link to item Cite

An ensemble neural network approach to forecast Dengue outbreak based on climatic condition

Journal Article Chaos Solitons and Fractals · February 1, 2023 Dengue fever is a virulent disease spreading over 100 tropical and subtropical countries in Africa, the Americas, and Asia. This arboviral disease affects around 400 million people globally, severely distressing the healthcare systems. The unavailability o ... Full text Cite

Adding heart rate n-variability (HRnV) to clinical assessment potentially improves prediction of serious bacterial infections in young febrile infants at the emergency department: a prospective observational study.

Journal Article Ann Transl Med · January 15, 2023 BACKGROUND: We aim to investigate the utility of heart rate variability (HRV) and heart rate n-variability (HRnV) in addition to vital signs and blood biomarkers, among febrile young infants at risk of serious bacterial infections (SBIs). METHODS: We perfo ... Full text Link to item Cite

The Effect of Building-Level Socioeconomic Status on Bystander Cardiopulmonary Resuscitation: A Retrospective Cohort Study.

Journal Article Prehosp Emerg Care · 2023 OBJECTIVE: Understanding the social determinants of bystander cardiopulmonary resuscitation (CPR) receipt can inform the design of public health interventions to increase bystander CPR. The association of socioeconomic status with bystander CPR is generall ... Full text Link to item Cite

Synthetic artificial intelligence using generative adversarial network for retinal imaging in detection of age-related macular degeneration.

Journal Article Front Med (Lausanne) · 2023 INTRODUCTION: Age-related macular degeneration (AMD) is one of the leading causes of vision impairment globally and early detection is crucial to prevent vision loss. However, the screening of AMD is resource dependent and demands experienced healthcare pr ... Full text Link to item Cite

A deep learning architecture for forecasting daily emergency department visits with acuity levels

Journal Article Chaos Solitons and Fractals · December 1, 2022 Accurate forecasting of Emergency Department (ED) visits is important for decision-making purposes in hospitals. It helps to form tactical and operational level plans, which facilitates staff and resource allocations in advance. A dataset recording the dai ... Full text Cite

AutoScore-Ordinal: an interpretable machine learning framework for generating scoring models for ordinal outcomes.

Journal Article BMC Med Res Methodol · November 4, 2022 BACKGROUND: Risk prediction models are useful tools in clinical decision-making which help with risk stratification and resource allocations and may lead to a better health care for patients. AutoScore is a machine learning-based automatic clinical score g ... Full text Link to item Cite

Benchmarking emergency department prediction models with machine learning and public electronic health records.

Journal Article Sci Data · October 27, 2022 The demand for emergency department (ED) services is increasing across the globe, particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have become increasingly challenging due to the shortage of medical resources and the s ... Full text Link to item Cite

An external validation study of the Score for Emergency Risk Prediction (SERP), an interpretable machine learning-based triage score for the emergency department.

Journal Article Sci Rep · October 19, 2022 Emergency departments (EDs) are experiencing complex demands. An ED triage tool, the Score for Emergency Risk Prediction (SERP), was previously developed using an interpretable machine learning framework. It achieved a good performance in the Singapore pop ... Full text Link to item Cite

Ambient Air Quality and Emergency Hospital Admissions in Singapore: A Time-Series Analysis.

Journal Article Int J Environ Res Public Health · October 16, 2022 Air pollution exposure may increase the demand for emergency healthcare services, particularly in South-East Asia, where the burden of air-pollution-related health impacts is high. This article aims to investigate the association between air quality and em ... Full text Link to item Cite

Association of air pollution with acute ischemic stroke risk in Singapore: a time-stratified case-crossover study.

Journal Article Int J Stroke · October 2022 BACKGROUND: Air quality is an important determinant of cardiovascular health such as ischemic heart disease and acute ischemic stroke (AIS) with substantial mortality and morbidity reported across the globe. However, associations between air quality and AI ... Full text Link to item Cite

The Role of Drones in Out-of-Hospital Cardiac Arrest: A Scoping Review.

Journal Article J Clin Med · September 28, 2022 Drones may be able to deliver automated external defibrillators (AEDs) directly to bystanders of out-of-hospital cardiac arrest (OHCA) events, improving survival outcomes by facilitating early defibrillation. We aimed to provide an overview of the availabl ... Full text Link to item Cite

Management of Out-of-Hospital Cardiac Arrest during COVID-19: A Tale of Two Cities.

Journal Article J Clin Med · September 1, 2022 Variations in the impact of the COVID-19 pandemic on out-of-hospital cardiac arrest (OHCA) have been reported. We aimed to, using population-based registries, compare community response, Emergency Medical Services (EMS) interventions and outcomes of adult, ... Full text Link to item Cite

Biomarker characterization of clinical subtypes of Parkinson Disease.

Journal Article NPJ Parkinsons Dis · August 29, 2022 The biological underpinnings of the PD clusters remain unknown as the existing PD clusters lacks biomarker characterization. We try to identify clinical subtypes of Parkinson Disease (PD) in an Asian cohort and characterize them by comparing clinical asses ... Full text Link to item Cite

Nationwide study of the characteristics of frequent attenders with multiple emergency department attendance patterns.

Journal Article Ann Acad Med Singap · August 2022 INTRODUCTION: The burden of frequent attenders (FAs) of emergency departments (EDs) on healthcare resources is underestimated when single-centre analyses do not account for utilisation of multiple EDs by FAs. We aimed to quantify the extent of multiple ED ... Full text Link to item Cite

Validation of the CaRdiac Arrest Survival Score (CRASS) for predicting good neurological outcome after out-of-hospital cardiac arrest in an Asian emergency medical service system.

Journal Article Resuscitation · July 2022 BACKGROUND: Survival with favorable neurological outcomes is an important indicator of successful resuscitation in out-of-hospital cardiac arrest (OHCA). We sought to validate the CaRdiac Arrest Survival Score (CRASS), derived using data from the German Re ... Full text Link to item Cite

Long term risk of recurrence among survivors of sudden cardiac arrest: A systematic review and meta-analysis.

Journal Article Resuscitation · July 2022 AIMS: With a growing number of survivors of sudden cardiac arrest globally, their natural disease progression is of interest. This systematic review and meta-analysis aimed to determine the risk of recurrence after sudden cardiac arrest and its associated ... Full text Link to item Cite

Predicting hospital emergency department visits with deep learning approaches

Journal Article Biocybernetics and Biomedical Engineering · July 1, 2022 Overcrowding in emergency department (ED) causes lengthy waiting times, reduces adequate emergency care and increases rate of mortality. Accurate prediction of daily ED visits and allocating resources in advance is one of the solutions to ED overcrowding p ... Full text Cite

Development and validation of an interpretable prehospital return of spontaneous circulation (P-ROSC) score for patients with out-of-hospital cardiac arrest using machine learning: A retrospective study.

Journal Article EClinicalMedicine · June 2022 BACKGROUND: Return of spontaneous circulation (ROSC) before arrival at the emergency department is an early indicator of successful resuscitation in out-of-hospital cardiac arrest (OHCA). Several ROSC prediction scores have been developed with European coh ... Full text Link to item Cite

A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study.

Journal Article PLOS Digit Health · June 2022 Risk scores are widely used for clinical decision making and commonly generated from logistic regression models. Machine-learning-based methods may work well for identifying important predictors to create parsimonious scores, but such 'black box' variable ... Full text Link to item Cite

Development and validation of an interpretable clinical score for early identification of acute kidney injury at the emergency department.

Journal Article Sci Rep · May 2, 2022 Acute kidney injury (AKI) in hospitalised patients is a common syndrome associated with poorer patient outcomes. Clinical risk scores can be used for the early identification of patients at risk of AKI. We conducted a retrospective study using electronic h ... Full text Link to item Cite

Association of High-Volume Centers With Survival Outcomes Among Patients With Nontraumatic Out-of-Hospital Cardiac Arrest: A Systematic Review and Meta-Analysis.

Journal Article JAMA Netw Open · May 2, 2022 IMPORTANCE: Although high volume of cases of out-of-hospital cardiac arrest (OHCA) is a key feature of cardiac arrest centers, which have proven survival benefit, the role of center volume as an independent variable associated with improved outcomes is unc ... Full text Link to item Cite

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.

Journal Article J Biomed Inform · May 2022 BACKGROUND: Medical decision-making impacts both individual and public health. Clinical scores are commonly used among various decision-making models to determine the degree of disease deterioration at the bedside. AutoScore was proposed as a useful clinic ... Full text Link to item Cite

Proper Use of Multiple Imputation and Dealing with Missing Covariate Data.

Journal Article World Neurosurg · May 2022 BACKGROUND: Missing data is a typical problem in clinical studies, where the value of variables of interest is not measured or collected for some patients. This article aimed to review imputation approaches for missing values and their application in neuro ... Full text Link to item Cite

Shapley variable importance cloud for interpretable machine learning.

Journal Article Patterns (N Y) · April 8, 2022 Interpretable machine learning has been focusing on explaining final models that optimize performance. The state-of-the-art Shapley additive explanations (SHAP) locally explains the variable impact on individual predictions and has recently been extended t ... Full text Link to item Cite

Leveraging Large-Scale Electronic Health Records and Interpretable Machine Learning for Clinical Decision Making at the Emergency Department: Protocol for System Development and Validation.

Journal Article JMIR Res Protoc · March 25, 2022 BACKGROUND: There is a growing demand globally for emergency department (ED) services. An increase in ED visits has resulted in overcrowding and longer waiting times. The triage process plays a crucial role in assessing and stratifying patients' risks and ... Full text Link to item Cite

Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions.

Journal Article EClinicalMedicine · March 2022 BACKGROUND: Emergency readmission poses an additional burden on both patients and healthcare systems. Risk stratification is the first step of transitional care interventions targeted at reducing readmission. To accurately predict the short- and intermedia ... Full text Link to item Cite

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies.

Journal Article J Biomed Inform · February 2022 OBJECTIVE: Temporal electronic health records (EHRs) contain a wealth of information for secondary uses, such as clinical events prediction and chronic disease management. However, challenges exist for temporal data representation. We therefore sought to i ... Full text Link to item Cite

Gender disparities among adult recipients of layperson bystander cardiopulmonary resuscitation by location of cardiac arrest in Pan-Asian communities: A registry-based study.

Journal Article EClinicalMedicine · February 2022 BACKGROUND: Bystander cardiopulmonary resuscitation (BCPR) is a critical component of the 'chain of survival' in reducing mortality among out-of-hospital cardiac arrest (OHCA) victims. Inconsistent findings on gender disparities among adult recipients of l ... Full text Link to item Cite

Impact of Cardiac Arrest Centers on the Survival of Patients With Nontraumatic Out-of-Hospital Cardiac Arrest: A Systematic Review and Meta-Analysis.

Journal Article J Am Heart Assoc · January 4, 2022 Background The role of cardiac arrest centers (CACs) in out-of-hospital cardiac arrest care systems is continuously evolving. Interpretation of existing literature is limited by heterogeneity in CAC characteristics and types of patients transported to CACs ... Full text Link to item Cite

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.

Journal Article J Biomed Inform · January 2022 BACKGROUND: Scoring systems are highly interpretable and widely used to evaluate time-to-event outcomes in healthcare research. However, existing time-to-event scores are predominantly created ad-hoc using a few manually selected variables based on clinici ... Full text Link to item Cite

Implementation of prediction models in the emergency department from an implementation science perspective-Determinants, outcomes and real-world impact: A scoping review protocol.

Journal Article PLoS One · 2022 The number of prediction models developed for use in emergency departments (EDs) have been increasing in recent years to complement traditional triage systems. However, most of these models have only reached the development or validation phase, and few hav ... Full text Link to item Cite

Development and validation of the SARICA score to predict survival after return of spontaneous circulation in out of hospital cardiac arrest using an interpretable machine learning framework.

Journal Article Resuscitation · January 2022 BACKGROUND: Accurate and timely prognostication of patients with out-of-hospital cardiac arrest (OHCA) who achieved the return of spontaneous circulation (ROSC) is crucial in clinical decision-making, resource allocation, and communications with next-of-ki ... Full text Link to item Cite

External validation of the Survival After ROSC in Cardiac Arrest (SARICA) score for predicting survival after return of spontaneous circulation using multinational pan-asian cohorts.

Journal Article Front Med (Lausanne) · 2022 AIM: Accurate and timely prognostication of patients with out-of-hospital cardiac arrest (OHCA) who attain return of spontaneous circulation (ROSC) is crucial in clinical decision-making, resource allocation, and communication with family. A clinical decis ... Full text Link to item Cite

Blood Lipid Biomarkers in Early Parkinson's Disease and Parkinson's Disease with Mild Cognitive Impairment.

Journal Article J Parkinsons Dis · 2022 BACKGROUND: Lipid biomarkers have potential neuroprotective effects in Parkinson's disease (PD) and there is limited evidence in the field. OBJECTIVE: This study aims to investigate the association between comprehensive blood lipid biomarkers and PD. METHO ... Full text Link to item Cite

Impact of the COVID-19 pandemic on the epidemiology of out-of-hospital cardiac arrest: a systematic review and meta-analysis.

Journal Article Ann Intensive Care · December 7, 2021 BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has significantly influenced epidemiology, yet its impact on out-of-hospital cardiac arrest (OHCA) remains unclear. We aimed to evaluate the impact of the pandemic on the incidence and case fatal ... Full text Link to item Cite

Trends of chronic illness in emergency department admissions among elderly adults in a tertiary hospital over ten years.

Journal Article BMC Health Serv Res · December 4, 2021 BACKGROUND: This study aimed to determine to what extent an aging population and shift to chronic illness has contributed to emergency admissions at a tertiary care hospital over ten years. METHODS: This was a retrospective observational study performed us ... Full text Link to item Cite

A clinical predictive model for risk stratification of patients with severe acute lower gastrointestinal bleeding.

Journal Article World J Emerg Surg · November 22, 2021 BACKGROUND: Lower gastrointestinal bleeding (LGIB) is a common presentation of surgical admissions, imposing a significant burden on healthcare costs and resources. There is a paucity of standardised clinical predictive tools available for the initial asse ... Full text Link to item Cite

Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions.

Journal Article JAMA Netw Open · August 2, 2021 IMPORTANCE: Triage in the emergency department (ED) is a complex clinical judgment based on the tacit understanding of the patient's likelihood of survival, availability of medical resources, and local practices. Although a scoring tool could be valuable i ... Full text Open Access Link to item Cite

Early prediction of serious infections in febrile infants incorporating heart rate variability in an emergency department: a pilot study.

Journal Article Emerg Med J · August 2021 BACKGROUND: Early differentiation of febrile young infants with from those without serious infections (SIs) remains a diagnostic challenge. We sought to (1) compare vital signs and heart rate variability (HRV) parameters between febrile infants with versus ... Full text Link to item Cite

Effective Treatment Recommendations for Type 2 Diabetes Management Using Reinforcement Learning: Treatment Recommendation Model Development and Validation.

Journal Article J Med Internet Res · July 22, 2021 BACKGROUND: Type 2 diabetes mellitus (T2DM) and its related complications represent a growing economic burden for many countries and health systems. Diabetes complications can be prevented through better disease control, but there is a large gap between th ... Full text Link to item Cite

Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review.

Journal Article Int J Environ Res Public Health · April 29, 2021 Background: Little is known about the role of artificial intelligence (AI) as a decisive technology in the clinical management of COVID-19 patients. We aimed to systematically review and critically appraise the current evidence on AI applications for COVID ... Full text Link to item Cite

Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department.

Journal Article BMC Med Res Methodol · April 17, 2021 BACKGROUND: Chest pain is among the most common presenting complaints in the emergency department (ED). Swift and accurate risk stratification of chest pain patients in the ED may improve patient outcomes and reduce unnecessary costs. Traditional logistic ... Full text Link to item Cite

Prediction of breakthrough pain during labour neuraxial analgesia: comparison of machine learning and multivariable regression approaches.

Journal Article Int J Obstet Anesth · February 2021 INTRODUCTION: Risk-prediction models for breakthrough pain facilitate interventions to forestall inadequate labour analgesia, but limited work has used machine learning to identify predictive factors. We compared the performance of machine learning and reg ... Full text Link to item Cite

Heart rate n-variability (HRnV) measures for prediction of mortality in sepsis patients presenting at the emergency department.

Journal Article PLoS One · 2021 Sepsis is a potentially life-threatening condition that requires prompt recognition and treatment. Recently, heart rate variability (HRV), a measure of the cardiac autonomic regulation derived from short electrocardiogram tracings, has been found to correl ... Full text Link to item Cite

Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission.

Journal Article Ann Surg · December 2020 OBJECTIVE: To compare the performance of machine learning models against the traditionally derived Combined Assessment of Risk Encountered in Surgery (CARES) model and the American Society of Anaesthesiologists-Physical Status (ASA-PS) in the prediction of ... Full text Link to item Cite

Analytics with artificial intelligence to advance the treatment of acute respiratory distress syndrome.

Journal Article J Evid Based Med · November 2020 Artificial intelligence (AI) has found its way into clinical studies in the era of big data. Acute respiratory distress syndrome (ARDS) or acute lung injury (ALI) is a clinical syndrome that encompasses a heterogeneous population. Management of such hetero ... Full text Link to item Cite

Individualized fluid administration for critically ill patients with sepsis with an interpretable dynamic treatment regimen model.

Journal Article Sci Rep · October 21, 2020 Fluid strategy is the key to the successful management of patients with sepsis. However, previous studies failed to consider individualized treatment strategy, and clinical trials typically included patients with sepsis as a homogeneous study population. W ... Full text Link to item Cite

AutoScore: A Machine Learning-Based Automatic Clinical Score Generator and Its Application to Mortality Prediction Using Electronic Health Records.

Journal Article JMIR Med Inform · October 21, 2020 BACKGROUND: Risk scores can be useful in clinical risk stratification and accurate allocations of medical resources, helping health providers improve patient care. Point-based scores are more understandable and explainable than other complex models and are ... Full text Link to item Cite

Risk stratification of patients with atrial fibrillation in the emergency department.

Journal Article Am J Emerg Med · September 2020 INTRODUCTION AND METHODS: Early and accurate risk stratification of patients with atrial fibrillation (AF) in the emergency department (ED) could aid the physician in determining a timely treatment strategy appropriate to the severity of disease. We conduc ... Full text Link to item Cite

Coronavirus disease 2019 (COVID-19): an evidence map of medical literature.

Journal Article BMC Med Res Methodol · July 2, 2020 BACKGROUND: Since the beginning of the COVID-19 outbreak in December 2019, a substantial body of COVID-19 medical literature has been generated. As of June 2020, gaps and longitudinal trends in the COVID-19 medical literature remain unidentified, despite p ... Full text Open Access Link to item Cite

Heart rate n-variability (HRnV) and its application to risk stratification of chest pain patients in the emergency department.

Journal Article BMC Cardiovasc Disord · April 10, 2020 BACKGROUND: Chest pain is one of the most common complaints among patients presenting to the emergency department (ED). Causes of chest pain can be benign or life threatening, making accurate risk stratification a critical issue in the ED. In addition to t ... Full text Link to item Cite

Validation of the ROSC after cardiac arrest (RACA) score in Pan-Asian out-of-hospital cardiac arrest patients.

Journal Article Resuscitation · April 2020 AIM: Survival is the most consistently captured outcome across countries for out-of-hospital cardiac arrests (OHCA), with return of spontaneous circulation (ROSC) representing the earliest endpoint for 'unbiased' initial resuscitation success. The ROSC aft ... Full text Link to item Cite

Impact of Air Pollution and Trans-Boundary Haze on Nation-Wide Emergency Department Visits and Hospital Admissions in Singapore.

Journal Article Ann Acad Med Singap · February 2020 INTRODUCTION: Air pollution is associated with adverse health outcomes. However, its impact on emergency health services is less well understood. We investigated the impact of air pollution on nation-wide emergency department (ED) visits and hospital admis ... Link to item Cite

Novel model for predicting inpatient mortality after emergency admission to hospital in Singapore: retrospective observational study.

Journal Article BMJ Open · September 26, 2019 OBJECTIVES: To identify risk factors for inpatient mortality after patients' emergency admission and to create a novel model predicting inpatient mortality risk. DESIGN: This was a retrospective observational study using data extracted from electronic heal ... Full text Open Access Link to item Cite

Predicting hospital admission at the emergency department triage: A novel prediction model.

Journal Article Am J Emerg Med · August 2019 BACKGROUND: Emergency department (ED) overcrowding is a growing international patient safety issue. A major contributor to overcrowding is long wait times for inpatient hospital admission. The objective of this study is to create a model that can predict a ... Full text Link to item Cite

Validation of the mortality in emergency department sepsis (MEDS) score in a Singaporean cohort.

Journal Article Medicine (Baltimore) · August 2019 The emergency department (ED) serves as the first point of hospital contact for most septic patients. Early mortality risk stratification using a quick and accurate triage tool would have great value in guiding management. The mortality in emergency depart ... Full text Link to item Cite

Mechanical power normalized to predicted body weight as a predictor of mortality in patients with acute respiratory distress syndrome.

Journal Article Intensive Care Med · June 2019 PURPOSE: Protective mechanical ventilation based on multiple ventilator parameters such as tidal volume, plateau pressure, and driving pressure has been widely used in acute respiratory distress syndrome (ARDS). More recently, mechanical power (MP) was fou ... Full text Link to item Cite

Combining Heart Rate Variability with Disease Severity Score Variables for Mortality Risk Stratification in Septic Patients Presenting at the Emergency Department.

Journal Article Int J Environ Res Public Health · May 16, 2019 The emergency department (ED) serves as the first point of hospital contact for many septic patients, where risk-stratification would be invaluable. We devised a combination model incorporating demographic, clinical, and heart rate variability (HRV) parame ... Full text Link to item Cite

Time-Stratified Case Crossover Study of the Association of Outdoor Ambient Air Pollution With the Risk of Acute Myocardial Infarction in the Context of Seasonal Exposure to the Southeast Asian Haze Problem.

Journal Article J Am Heart Assoc · March 19, 2019 Background Prior studies have demonstrated the association of air pollution with cardiovascular deaths. Singapore experiences seasonal transboundary haze. We investigated the association between air pollution and acute myocardial infarction ( AMI ) inciden ... Full text Link to item Cite

Outcomes and modifiable resuscitative characteristics amongst pan-Asian out-of-hospital cardiac arrest occurring at night.

Journal Article Medicine (Baltimore) · March 2019 Studies are divided on the effect of day-night temporal differences on clinical outcomes in out-of-hospital cardiac arrest (OHCA). This study aimed to elucidate any differences in OHCA survival between day and night occurrence, and the factors associated w ... Full text Link to item Cite

Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department.

Journal Article Medicine (Baltimore) · February 2019 Early identification of high-risk septic patients in the emergency department (ED) may guide appropriate management and disposition, thereby improving outcomes. We compared the performance of machine learning models against conventional risk stratification ... Full text Link to item Cite

Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients.

Journal Article Burns Trauma · 2019 BACKGROUND: Triage trauma scores are utilised to determine patient disposition, interventions and prognostication in the care of trauma patients. Heart rate variability (HRV) and heart rate complexity (HRC) reflect the autonomic nervous system and are deri ... Full text Link to item Cite

Combining quick sequential organ failure assessment score with heart rate variability may improve predictive ability for mortality in septic patients at the emergency department.

Journal Article PLoS One · 2019 BACKGROUND: Although the quick Sequential Organ Failure Assessment (qSOFA) score was recently introduced to identify patients with suspected infection/sepsis, it has limitations as a predictive tool for adverse outcomes. We hypothesized that combining qSOF ... Full text Link to item Cite

Health impacts of the Southeast Asian haze problem - A time-stratified case crossover study of the relationship between ambient air pollution and sudden cardiac deaths in Singapore.

Journal Article Int J Cardiol · November 15, 2018 OBJECTIVES: To investigate the association between air pollution and out-of-hospital cardiac arrest (OHCA) incidence in Singapore. DESIGN: A time-stratified case-crossover design study. SETTING: OHCA incidences of all etiology in Singapore. PARTICIPANTS: 8 ... Full text Link to item Cite

The Relationship Between Ambient Air Pollution and Acute Ischemic Stroke: A Time-Stratified Case-Crossover Study in a City-State With Seasonal Exposure to the Southeast Asian Haze Problem.

Journal Article Ann Emerg Med · November 2018 STUDY OBJECTIVE: Studies are divided on the short-term association of air pollution with stroke. Singapore is exposed to seasonal transboundary haze. We aim to investigate the association between air pollution and stroke incidence in Singapore. METHODS: We ... Full text Link to item Cite

A novel heart rate variability based risk prediction model for septic patients presenting to the emergency department.

Journal Article Medicine (Baltimore) · June 2018 A quick, objective, non-invasive means of identifying high-risk septic patients in the emergency department (ED) can improve hospital outcomes through early, appropriate management. Heart rate variability (HRV) analysis has been correlated with mortality i ... Full text Link to item Cite

The top 2,000 cited articles in critical care medicine: a bibliometric analysis.

Journal Article J Thorac Dis · April 2018 BACKGROUND: The bibliometric analysis has been performed on several topics in critical care medicine (CCM) focusing on top 100 cited articles, but the analysis on CCM literature as a whole is missing. The present study aimed to perform a complete bibliomet ... Full text Link to item Cite

Data-Driven Approach to Defining the Emergency Department Frequent Attender Using a Cohort of 10 Years.

Journal Article J Acute Med · March 1, 2018 AIMS: To identify, based on the measure of resource utilization, the number of visits per calendar year that defines the emergency department (ED) frequent attender; and examine for significant trends in patient characteristics and outcomes which may suppo ... Full text Link to item Cite

Heart Rate Variability Analysis in Patients Who Have Bradycardia Presenting to the Emergency Department with Chest Pain.

Journal Article J Emerg Med · March 2018 BACKGROUND: Heart rate variability (HRV) is a noninvasive method to measure the function of the autonomic nervous system. It has been used to risk stratify patients with undifferentiated chest pain in the emergency department (ED). However, bradycardia can ... Full text Link to item Cite

Integrating heart rate variability, vital signs, electrocardiogram, and troponin to triage chest pain patients in the ED.

Journal Article Am J Emerg Med · February 2018 BACKGROUND: Current triage methods for chest pain patients typically utilize symptoms, electrocardiogram (ECG), and vital sign data, requiring interpretation by dedicated triage clinicians. In contrast, we aimed to create a quickly obtainable model integra ... Full text Link to item Cite

Frequent hospital admissions in Singapore: clinical risk factors and impact of socioeconomic status.

Journal Article Singapore Med J · January 2018 INTRODUCTION: Frequent admitters to hospitals are high-cost patients who strain finite healthcare resources. However, the exact risk factors for frequent admissions, which can be used to guide risk stratification and design effective interventions locally, ... Full text Link to item Cite

Association between the elderly frequent attender to the emergency department and 30-day mortality: A retrospective study over 10 years.

Journal Article World J Emerg Med · 2018 BACKGROUND: To determine if elderly frequent attenders are associated with increased 30-day mortality, assess resource utilization by the elderly frequent attenders and identify associated characteristics that contribute to mortality. METHODS: Retrospectiv ... Full text Link to item Cite

Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore.

Journal Article BMC Health Serv Res · November 23, 2017 BACKGROUND: Segmenting the population into groups that are relatively homogeneous in healthcare characteristics or needs is crucial to facilitate integrated care and resource planning. We aimed to evaluate the feasibility of segmenting the population into ... Full text Link to item Cite

Extreme learning machine based mutual information estimation with application to time-series change-points detection

Journal Article Neurocomputing · October 25, 2017 In this paper, we propose an efficient parameter tuning-free squared-loss mutual information (SMI) estimator in a form of a radial basis function (RBF) network. The input layer of the proposed network propagates a sample pair of two random variables to the ... Full text Cite

Reperfusion treatment delays amongst patients with painless ST segment elevation myocardial infarction.

Journal Article CJEM · September 2017 OBJECTIVE: Early reperfusion therapy in the treatment of ST segment elevation myocardial infarction (STEMI) patients can improve outcomes. Silent myocardial infarction is associated with poor prognosis, but little is known about its effect on treatment del ... Full text Link to item Cite

Ensemble-Based Risk Scoring with Extreme Learning Machine for Prediction of Adverse Cardiac Events

Journal Article Cognitive Computation · August 1, 2017 Accurate prediction of adverse cardiac events for the emergency department (ED) chest pain patients is essential in risk stratification due to the current ambiguity in diagnosing acute coronary syndrome. While most current practices rely on human decision ... Full text Cite

Electric bicycle-related injuries presenting to a provincial hospital in China: A retrospective study.

Journal Article Medicine (Baltimore) · June 2017 The use of electric bicycles (EBs) in China is growing. In the present study, we aimed to characterize the pattern and outcomes of EB-related injuries presenting to a major general hospital in China.This was a retrospective review of EB-related injuries pr ... Full text Link to item Cite

Performance of the LACE index to identify elderly patients at high risk for hospital readmission in Singapore.

Journal Article Medicine (Baltimore) · May 2017 Unplanned readmissions may be avoided by accurate risk prediction and appropriate resources could be allocated to high risk patients. The Length of stay, Acuity of admission, Charlson comorbidity index, Emergency department visits in past six months (LACE) ... Full text Link to item Cite

FAM-FACE-SG: a score for risk stratification of frequent hospital admitters.

Journal Article BMC Med Inform Decis Mak · April 8, 2017 BACKGROUND: An accurate risk stratification tool is critical in identifying patients who are at high risk of frequent hospital readmissions. While 30-day hospital readmissions have been widely studied, there is increasing interest in identifying potential ... Full text Link to item Cite

Comparing HEART, TIMI, and GRACE scores for prediction of 30-day major adverse cardiac events in high acuity chest pain patients in the emergency department.

Journal Article Int J Cardiol · October 15, 2016 BACKGROUND: The HEART, TIMI, and GRACE scores have been applied in the Emergency Department (ED) to risk stratify patients with undifferentiated chest pain. This study aims to compare the accuracy of HEART, TIMI, and GRACE for the prediction of major adver ... Full text Link to item Cite

Predicting frequent hospital admission risk in Singapore: a retrospective cohort study to investigate the impact of comorbidities, acute illness burden and social determinants of health.

Journal Article BMJ Open · October 14, 2016 OBJECTIVES: To evaluate the impact of comorbidities, acute illness burden and social determinants of health on predicting the risk of frequent hospital admissions. DESIGN: Multivariable logistic regression was used to associate the predictive variables ext ... Full text Link to item Cite

A novel cardiovascular risk stratification model incorporating ECG and heart rate variability for patients presenting to the emergency department with chest pain.

Journal Article Crit Care · June 11, 2016 BACKGROUND: Risk stratification models can be employed at the emergency department (ED) to evaluate patient prognosis and guide choice of treatment. We derived and validated a new cardiovascular risk stratification model comprising vital signs, heart rate ... Full text Link to item Cite

Characteristics of patients who made a return visit within 72 hours to the emergency department of a Singapore tertiary hospital.

Journal Article Singapore Med J · June 2016 INTRODUCTION: 72-hour emergency department (ED) reattendance is a widely-used quality indicator for quality of care and patient safety. It is generally assumed that patients who return within 72 hours of ED discharge (72-hour re-attendees) received inadequ ... Full text Link to item Cite

Associations between gender and cardiac arrest outcomes in Pan-Asian out-of-hospital cardiac arrest patients.

Journal Article Resuscitation · May 2016 BACKGROUND: The incidence of out-of-hospital cardiac arrest (OHCA) in women is thought to be lower than that of men, with better outcomes in some Western studies. OBJECTIVES: This study aimed to investigate the effect of gender on OHCA outcomes in the Pan- ... Full text Link to item Cite

A prospective surveillance of paediatric head injuries in Singapore: a dual-centre study.

Journal Article BMJ Open · February 23, 2016 OBJECTIVE: To study the causes of head injuries among the paediatric population in Singapore, and the association between causes and mortality, as well as the need for airway or neurosurgical intervention. DESIGN: This is a prospective observational study ... Full text Link to item Cite

Predicting 30-Day Readmissions in an Asian Population: Building a Predictive Model by Incorporating Markers of Hospitalization Severity.

Journal Article PLoS One · 2016 BACKGROUND: To reduce readmissions, it may be cost-effective to consider risk stratification, with targeting intervention programs to patients at high risk of readmissions. In this study, we aimed to derive and validate a prediction model including several ... Full text Link to item Cite

Housing as a Social Determinant of Health in Singapore and Its Association with Readmission Risk and Increased Utilization of Hospital Services.

Journal Article Front Public Health · 2016 BACKGROUND: Residence in public rental housing is an area-level measure of socioeconomic status, but its impact as a social determinant of health in Singapore has not been studied. We therefore aimed to examine the association of public rental housing with ... Full text Link to item Cite

Emergency Medical Services Utilization among Patients with ST-Segment Elevation Myocardial Infarction: Observations from the Singapore Myocardial Infarction Registry.

Journal Article Prehosp Emerg Care · 2016 OBJECTIVE: Early activation of emergency medical services (EMS), rapid transport, and treatment of patients experiencing ST-segment elevation myocardial infarction (STEMI) can improve outcomes. The Singapore Myocardial Infarction Registry (SMIR) is a natio ... Full text Link to item Cite

Manifold ranking based scoring system with its application to cardiac arrest prediction: A retrospective study in emergency department patients.

Journal Article Comput Biol Med · December 1, 2015 BACKGROUND: The recently developed geometric distance scoring system has shown the effectiveness of scoring systems in predicting cardiac arrest within 72h and the potential to predict other clinical outcomes. However, the geometric distance scoring system ... Full text Link to item Cite

Landmark recognition with sparse representation classification and extreme learning machine

Journal Article Journal of the Franklin Institute · October 1, 2015 Along with the rapid development of intelligent mobile terminals, applications on landmark recognition attract increasingly attentions by world wide researchers in the past several years. Although promising achievements have been presented, designing a rob ... Full text Cite

Predictors for moderate to severe paediatric head injury derived from a surveillance registry in the emergency department.

Journal Article Injury · July 2015 INTRODUCTION AND AIM: Head injuries are a common complaint among children presenting to the emergency department (ED). This study is part of an ongoing prospective surveillance of head injured children presenting to a paediatric ED. We aim to derive predic ... Full text Link to item Cite

Predictive modeling in pediatric traumatic brain injury using machine learning.

Journal Article BMC Med Res Methodol · March 17, 2015 BACKGROUND: Pediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic challenge in the emergency department (ED). While large North American research networks have derived clinical prediction rules for the head injured child, t ... Full text Link to item Cite

Ensemble of subset online sequential extreme learning machine for class imbalance and concept drift

Journal Article Neurocomputing · February 3, 2015 In this paper, a computationally efficient framework, referred to as ensemble of subset online sequential extreme learning machine (ESOS-ELM), is proposed for class imbalance learning from a concept-drifting data stream. The proposed framework comprises a ... Full text Cite

Predicting 30-Day Readmissions: Performance of the LACE Index Compared with a Regression Model among General Medicine Patients in Singapore.

Journal Article Biomed Res Int · 2015 The LACE index (length of stay, acuity of admission, Charlson comorbidity index, CCI, and number of emergency department visits in preceding 6 months) derived in Canada is simple and may have clinical utility in Singapore to predict readmission risk. We co ... Full text Link to item Cite

Risk scoring for prediction of acute cardiac complications from imbalanced clinical data.

Journal Article IEEE J Biomed Health Inform · November 2014 Fast and accurate risk stratification is essential in the emergency department (ED) as it allows clinicians to identify chest pain patients who are at high risk of cardiac complications and require intensive monitoring and early intervention. In this paper ... Full text Link to item Cite

Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection.

Journal Article BMC Med Inform Decis Mak · August 23, 2014 BACKGROUND: The key aim of triage in chest pain patients is to identify those with high risk of adverse cardiac events as they require intensive monitoring and early intervention. In this study, we aim to discover the most relevant variables for risk predi ... Full text Link to item Cite

Evolutionary voting-based extreme learning machines

Journal Article Mathematical Problems in Engineering · January 1, 2014 Voting-based extreme learning machine (V-ELM) was proposed to improve learning efficiency where majority voting was employed. V-ELM assumes that all individual classifiers contribute equally to the decision ensemble. However, in many real-world scenarios, ... Full text Cite

Risk stratification with extreme learning machine: A retrospective study on emergency department patients

Journal Article Mathematical Problems in Engineering · January 1, 2014 This paper presents a novel risk stratification method using extreme learning machine (ELM). ELM was integrated into a scoring system to identify the risk of cardiac arrest in emergency department (ED) patients. The experiments were conducted on a cohort o ... Full text Cite

Evolutionary extreme learning machine and its application to image analysis

Journal Article Journal of Signal Processing Systems · October 1, 2013 Extreme learning machine (ELM) and evolutionary ELM (E-ELM) were proposed as a new class of learning algorithm for single-hidden layer feedforward neural network (SLFN). In order to achieve good generalization performance, E-ELM calculates the error on a s ... Full text Cite

An intelligent scoring system and its application to cardiac arrest prediction.

Journal Article IEEE Trans Inf Technol Biomed · November 2012 Traditional risk score prediction is based on vital signs and clinical assessment. In this paper, we present an intelligent scoring system for the prediction of cardiac arrest within 72 h. The patient population is represented by a set of feature vectors, ... Full text Link to item Cite

Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability compared with the modified early warning score.

Journal Article Crit Care · June 21, 2012 INTRODUCTION: A key aim of triage is to identify those with high risk of cardiac arrest, as they require intensive monitoring, resuscitation facilities, and early intervention. We aim to validate a novel machine learning (ML) score incorporating heart rate ... Full text Link to item Cite

Voting based extreme learning machine

Journal Article Information Sciences · February 15, 2012 This paper proposes an improved learning algorithm for classification which is referred to as voting based extreme learning machine. The proposed method incorporates the voting method into the popular extreme learning machine (ELM) in classification applic ... Full text Cite

Weighted principal component extraction with genetic algorithms

Journal Article Applied Soft Computing Journal · February 1, 2012 Pattern recognition techniques have been widely used in a variety of scientific disciplines including computer vision, artificial intelligence, biology, and so forth. Although many methods present satisfactory performances, they still have several weak poi ... Full text Cite

Patient outcome prediction with heart rate variability and vital signs

Journal Article Journal of Signal Processing Systems · August 1, 2011 The ability to predict patient outcomes is important for clinical triage, which is the process of assessing severity and assigning appropriate priority of treatment for large numbers of patients. In this study, we present an automatic prognosis system for ... Full text Cite

Ensemble based extreme learning machine

Journal Article IEEE Signal Processing Letters · July 9, 2010 Extreme learning machine (ELM) was proposed as a new class of learning algorithm for single-hidden layer feedforward neural network (SLFN). To achieve good generalization performance, ELM minimizes training error on the entire training data set, therefore ... Full text Cite

Modeling images with multiple trace transforms for pattern analysis

Journal Article IEEE Signal Processing Letters · April 16, 2009 Taking advantage of the various available Trace transforms generated from a single image, the multiple Trace feature (MTF) is proposed as a new image representation. In the process of MTF construction, genetic algorithms (GAs) play a key role as an informa ... Full text Cite

Improving predictive accuracy by evolving feature selection for face recognition

Journal Article IEICE Electronics Express · December 25, 2008 Face recognition system usually consists of feature extraction and pattern classification. However, not all of extracted facial features contribute to the classification positively because of the variations of illumination and poses in face images. In this ... Full text Cite