Monica Agrawal

Journal article NPJ Digit Med · October 7, 2025 While large language models (LLMs) hold promise for transforming clinical healthcare, current comparisons and benchmark evaluations of large language models in medicine often fail to capture real-world efficacy. Specifically, we highlight how key discrepan ... Full text Link to item Cite

An evaluation framework for ambient digital scribing tools in clinical applications.

Journal article NPJ Digit Med · June 13, 2025 Ambient digital scribing (ADS) tools alleviate clinician documentation burden, reducing burnout and enhancing efficiency. As AI-driven ADS tools integrate into clinical workflows, robust governance is essential for ethical and secure deployment. This study ... Full text Link to item Cite

Application of unified health large language model evaluation framework to In-Basket message replies: bridging qualitative and quantitative assessments.

Journal article J Am Med Inform Assoc · April 1, 2025 OBJECTIVES: Large language models (LLMs) are increasingly utilized in healthcare, transforming medical practice through advanced language processing capabilities. However, the evaluation of LLMs predominantly relies on human qualitative assessment, which i ... Full text Link to item Cite

Using Large Language Models to Promote Health Equity

Journal article NEJM AI · January 23, 2025 Full text Cite

Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing.

Journal article J Am Med Inform Assoc · June 20, 2024 OBJECTIVE: Leverage electronic health record (EHR) audit logs to develop a machine learning (ML) model that predicts which notes a clinician wants to review when seeing oncology patients. MATERIALS AND METHODS: We trained logistic regression models using n ... Full text Link to item Cite

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer.

Journal article JCO Clin Cancer Inform · May 2021 PURPOSE: Key oncology end points are not routinely encoded into electronic medical records (EMRs). We assessed whether natural language processing (NLP) can abstract treatment discontinuation rationale from unstructured EMR notes to estimate toxicity incid ... Full text Link to item Cite

Modeling polypharmacy side effects with graph convolutional networks.

Journal article Bioinformatics · July 1, 2018 MOTIVATION: The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases or co-existing conditions. However, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient. Polyphar ... Full text Link to item Cite