Assessing the Potential of GPT-4 to Annotate Medical Notes Across Different Languages and Countries: A Model Evaluation Study

Author:

Saad Menezes Maria Clara,Hoffmann Alexander F.,Tan Amelia LM,Nalbandyan Marine,Omenn Gilbert S.,Mazzotti Diego,Hernández-Arango Alejandro,Visweswaran Shyam,Venkatesh Shruthi,Mandl Kenneth D.,Bourgeois Florence T.,Lee James WK,Makmur Andrew,Hanauer David A.,Semanik Michael G.,Kerivan Lauren T.,Hill Terra,Forero Julian,Restrepo Castro Carlos Andrés CR,Vigna Matteo,Ceriana Piero,Abu-el-rub Noor,Avillach Paul,Bellazzi Riccardo,Callaci Thomas,Gutiérrez-Sacristán Alba,Malovini Alberto,Mathew Jomol P.,Morris Michele,Murthy Venkatesh,Parimbelli Enea,Patel Lav P.,Sáez Carlos,Samayamuthu Malarkodi Jebathilagam,Thompson Jeffrey,Tibollo Valentina,Xia Zongqi,Kohane Isaac,anon The Consortium for Clinical

Publisher

Elsevier BV

Reference15 articles.

1. Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review;S Sheikhalishahi;JMIR Med Inform,2019

2. Electronic Health Records: The Signal and the Noise;L B Russell;Medical Decision Making,2021

3. Large Language Models are Few-Shot Clinical Information Extractors;M Agrawal;arXiv,2023

4. Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges;H Ahsan;arXiv,2024

5. Large language models to identify social determinants of health in electronic health records. npj Digit;M Guevara;Med,2024

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