• A Albaladejo, A Lorleac'h, and J-S Allain.
• Médecine interne et immunologie clinique, CHU de Rennes, 2, rue Henri-le-Guilloux, 35000 Rennes, France. Electronic address: adrien.albaladejo@chu-rennes.fr.
• Rev Med Interne. 2024 Jul 1; 45 (7): 409414409-414.

IntroductionThe "Printemps de la Médecine Interne" are training days for Francophone internists. The clinical cases presented during these days are complex. This study aims to evaluate the diagnostic capabilities of non-specialized artificial intelligence (language models) ChatGPT-4 and Bard by confronting them with the puzzles of the "Printemps de la Médecine Interne".MethodClinical cases from the "Printemps de la Médecine Interne" 2021 and 2022 were submitted to two language models: ChatGPT-4 and Bard. In case of a wrong answer, a second attempt was offered. We then compared the responses of human internist experts to those of artificial intelligence.ResultsOf the 12 clinical cases submitted, human internist experts diagnosed nine, ChatGPT-4 diagnosed three, and Bard diagnosed one. One of the cases solved by ChatGPT-4 was not solved by the internist expert. The artificial intelligence had a response time of a few seconds.ConclusionsCurrently, the diagnostic skills of ChatGPT-4 and Bard are inferior to those of human experts in solving complex clinical cases but are very promising. Recently made available to the general public, they already have impressive capabilities, questioning the role of the diagnostic physician. It would be advisable to adapt the rules or subjects of future "Printemps de la Médecine Interne" so that they are not solved by a public language model.Copyright © 2024 The Author(s). Published by Elsevier Masson SAS.. All rights reserved.

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