Journal of the American Medical Informatics Association : JAMIA
Mar 1, 2025
OBJECTIVE: This study evaluates the utility of word embeddings, generated by large language models (LLMs), for medical diagnosis by comparing the semantic proximity of symptoms to their eponymic disease embedding ("eponymic condition") and the mean o...
Journal of the American Medical Informatics Association : JAMIA
Mar 1, 2025
OBJECTIVE: Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automating real-world tasks, their capabilities for healthcare appl...
Journal of the American Medical Informatics Association : JAMIA
Mar 1, 2025
OBJECTIVES: Clinical trials (CTs) are essential for improving patient care by evaluating new treatments' safety and efficacy. A key component in CT protocols is the study population defined by the eligibility criteria. This study aims to evaluate the...
MOTIVATION: LLMs like GPT-4, despite their advancements, often produce hallucinations and struggle with integrating external knowledge effectively. While Retrieval-Augmented Generation (RAG) attempts to address this by incorporating external informat...
Background Incomplete clinical histories are a well-known problem in radiology. Previous dedicated quality improvement efforts focusing on reproducible assessments of the completeness of free-text clinical histories have relied on tedious manual anal...
Journal of the American Medical Informatics Association : JAMIA
Feb 1, 2025
OBJECTIVES: We evaluate the effectiveness of large language models (LLMs), specifically GPT-based (GPT-3.5 and GPT-4) and Llama-2 models (13B and 7B architectures), in autonomously assessing clinical records (CRs) to enhance medical education and dia...
IMPORTANCE: Large language models (LLMs) can assist in various health care activities, but current evaluation approaches may not adequately identify the most useful application areas.
Journal of the Medical Library Association : JMLA
Jan 14, 2025
This project investigated the potential of generative AI models in aiding health sciences librarians with collection development. Researchers at Chapman University's Harry and Diane Rinker Health Science campus evaluated four generative AI models-Cha...
Journal of the Medical Library Association : JMLA
Jan 14, 2025
OBJECTIVE: This study investigated the performance of a generative artificial intelligence (AI) tool using GPT-4 in answering clinical questions in comparison with medical librarians' gold-standard evidence syntheses.