Evaluating Large Language Models in extracting cognitive exam dates and scores.

Evaluating Large Language Models in extracting cognitive exam dates and scores.

Ensuring reliability of Large Language Models (LLMs) in clinical tasks is crucial. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR. Our data consisted of 135,307 clinical notes (Jan 12th, 2010 to Ma...

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Main Authors: Hao Zhang, Neil Jethani, Simon Jones, Nicholas Genes, Vincent J Major, Ian S Jaffe, Anthony B Cardillo, Noah Heilenbach, Nadia Fazal Ali, Luke J Bonanni, Andrew J Clayburn, Zain Khera, Erica C Sadler, Jaideep Prasad, Jamie Schlacter, Kevin Liu, Benjamin Silva, Sophie Montgomery, Eric J Kim, Jacob Lester, Theodore M Hill, Alba Avoricani, Ethan Chervonski, James Davydov, William Small, Eesha Chakravartty, Himanshu Grover, John A Dodson, Abraham A Brody, Yindalon Aphinyanaphongs, Arjun Masurkar, Narges Razavian
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-12-01
Series:PLOS Digital Health
Online Access:https://doi.org/10.1371/journal.pdig.0000685
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https://doi.org/10.1371/journal.pdig.0000685

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