Data Mining

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  Subject Areas on Research

  • A cross-sectional analysis of HIV and hepatitis C clinical trials 2007 to 2010: the relationship between industry sponsorship and randomized study design. 
  • A qualitative analysis of nursing students' tweets during the COVID-19 pandemic. 
  • Affinity Chart Analysis: A Method for Structured Collection, Aggregation, and Response to Customer Needs in Radiology. 
  • Age-related differences in reporting of drug-associated liver injury: data-mining of WHO Safety Report Database. 
  • An atlas of genetic influences on human blood metabolites. 
  • Analysing breast cancer microarrays from African Americans using shrinkage-based discriminant analysis. 
  • Annotation of phenotypes using ontologies: a gold standard for the training and evaluation of natural language processing systems. 
  • Archeological Echocardiography: Digitization and Speckle Tracking Analysis of Archival Echocardiograms in the HyperGEN Study. 
  • Ascertainment of colonoscopy indication using administrative data. 
  • Atypical antipsychotic drugs and diabetes mellitus in the US Food and Drug Administration Adverse Event database: a systematic Bayesian signal detection analysis. 
  • Automated versus Manual Data Extraction of the Padua Prediction Score for Venous Thromboembolism Risk in Hospitalized Older Adults. 
  • Bioinformatic challenges in targeted proteomics. 
  • CKD as a Model for Improving Chronic Disease Care through Electronic Health Records. 
  • COMPASS-CP: An Electronic Application to Capture Patient-Reported Outcomes to Develop Actionable Stroke and Transient Ischemic Attack Care Plans. 
  • Comedications alter drug-induced liver injury reporting frequency: Data mining in the WHO VigiBase™. 
  • Comparison of Outcomes Following a Switch From a Brand to an Authorized Versus Independent Generic Drug. 
  • Computable Phenotype Implementation for a National, Multicenter Pragmatic Clinical Trial: Lessons Learned From ADAPTABLE. 
  • Culture counts--sustainable inpatient computerized surveillance across Duke University Health System. 
  • Curating a knowledge base for individuals with coinfection of HIV and SARS-CoV-2: a study protocol of EHR-based data mining and clinical implementation. 
  • Data mining in psychological treatment research: a primer on classification and regression trees. 
  • Design and Implementation of a Comprehensive Surveillance System for Venous Thromboembolism in a Defined Region Using Electronic and Manual Approaches. 
  • Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study. 
  • Electronic health records to facilitate clinical research. 
  • Evaluative Outcomes in Direct Extraction and Use of EHR Data in Clinical Trials. 
  • Four health data networks illustrate the potential for a shared national multipurpose big-data network. 
  • GREAT improves functional interpretation of cis-regulatory regions. 
  • Generating a focused view of disease ontology cancer terms for pan-cancer data integration and analysis. 
  • Genomics, clinical research, and learning health care systems: Strategies to improve patient care. 
  • Implementation of an Automated Radiology Recommendation-Tracking Engine for Abdominal Imaging Findings of Possible Cancer. 
  • Large clinical databases for the study of lung cancer: Making up for the failure of randomized trials. 
  • Large-scale evaluation of automated clinical note de-identification and its impact on information extraction. 
  • MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations. 
  • Mining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study. 
  • Moving the mountain: analysis of the effort required to transform comparative anatomy into computable anatomy. 
  • Multiscale gigapixel photography. 
  • Natural variation in CDC28 underlies morphological phenotypes in an environmental yeast isolate. 
  • Near-term prediction of sudden cardiac death in older hemodialysis patients using electronic health records. 
  • Neuropsychiatric adverse effects of oseltamivir in the FDA Adverse Event Reporting System, 1999-2012. 
  • Opportunities for the Cardiovascular Community in the Precision Medicine Initiative. 
  • Pediatric post-marketing safety systems in North America: assessment of the current status. 
  • Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield. 
  • Predicting mortality over different time horizons: which data elements are needed? 
  • Prevalence of Underdiagnosed Fragile X Syndrome in 2 Health Systems. 
  • Registry Assessment of Peripheral Interventional Devices (RAPID): Registry assessment of peripheral interventional devices core data elements. 
  • Relational machine learning for electronic health record-driven phenotyping. 
  • Reply to Comment on "Use of Patient Registries and Administrative Datasets for the Study of Pediatric Cancer". 
  • Report of the National Heart, Lung, and Blood Institute Working Group: An Integrated Network for Congenital Heart Disease Research. 
  • Selection of Informative Examples in Chemogenomic Datasets. 
  • SplicerAV: a tool for mining microarray expression data for changes in RNA processing. 
  • Strategies for delivering value from digital technology transformation. 
  • Text data extraction for a prospective, research-focused data mart: implementation and validation. 
  • The PCORnet Blood Pressure Control Laboratory: A Platform for Surveillance and Efficient Trials. 
  • The coming age of data-driven medicine: translational bioinformatics' next frontier. 
  • The influence of drug properties and host factors on delayed onset of symptoms in drug-induced liver injury. 
  • The use of big data in manual physiotherapy. 
  • Thoroughly modern risk prediction? 
  • Uncovering cyberincivility among nurses and nursing students on Twitter: A data mining study. 
  • Use of Natural Language Processing to Improve Identification of Patients With Peripheral Artery Disease. 
  • Use of patient registries and administrative datasets for the study of pediatric cancer. 
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  Keywords of People

  • Ma, Li, Associate Professor of Statistical Science, Biostatistics & Bioinformatics
  • Pang, Herbert, Adjunct Assistant Professor in the Department of Biostatistics & Bioinformatics, Biostatistics & Bioinformatics
  • Rusincovitch, Shelley, Senior Dir, IT, Biostatistics & Bioinformatics
  • Tenenbaum, Jessica Dale, Assistant Professor of Biostatistics & Bioinformatics, Duke Science & Society
  • Tsalik, Ephraim, Adjunct Associate Professor in the Department of Medicine, Medicine, Infectious Diseases