Evaluating a large language model’s ability to answer clinicians’ requests for evidence summaries

Evaluating a large language model’s ability to answer clinicians’ requests for evidence summaries

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. Methods: Questions were extracted from an in-house database of clinical evidenc...

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Bibliographic Details
Main Authors: Mallory N. Blasingame, Taneya Y. Koonce, Annette M. Williams, Dario A. Giuse, Jing Su, Poppy A. Krump, Nunzia Bettinsoli Giuse
Format: Article
Language:English
Published: University Library System, University of Pittsburgh 2025-01-01
Series:Journal of the Medical Library Association
Subjects:
Large Language Models
LLMs
Generative AI
Artificial Intelligence
Evidence Synthesis
Library Science
Online Access:http://jmla.pitt.edu/ojs/jmla/article/view/1985
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http://jmla.pitt.edu/ojs/jmla/article/view/1985

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