4 papers
Clinical Document Metadata Extraction: A Scoping Review
Kurt Miller, Qiuhao Lu, William Hersh +4
Clinical document metadata, such as document type, structure, author role, medical specialty, and encounter setting, is essential for accurate interpretation of information capture…
Gender-Neutral Large Language Models for Medical Applications: Reducing Bias in PubMed Abstracts
Elizabeth Schaefer, Kirk Roberts
This paper presents a pipeline for mitigating gender bias in large language models (LLMs) used in medical literature by neutralizing gendered occupational pronouns. A dataset of 37…
Overview of TREC 2024 Biomedical Generative Retrieval (BioGen) Track
Deepak Gupta, Dina Demner-Fushman, William Hersh +2
With the advancement of large language models (LLMs), the biomedical domain has seen significant progress and improvement in multiple tasks such as biomedical question answering, l…
Question Answering for Electronic Health Records: A Scoping Review of datasets and models
Jayetri Bardhan, Kirk Roberts, Daisy Zhe Wang
Question Answering (QA) systems on patient-related data can assist both clinicians and patients. They can, for example, assist clinicians in decision-making and enable patients to…