• T Pelaccia, G Forestier, and C Wemmert.
• Centre de formation et de recherche en pédagogie des sciences de la santé, faculté de médecine, université de Strasbourg, 4, rue Kirschleger, 67085 Strasbourg cedex, France; SAMU 67, hôpitaux universitaires de Strasbourg, 1, place de l'Hôpital, 67091 Strasbourg cedex, France. Electronic address: pelaccia@unistra.fr.
• Rev Med Interne. 2020 Mar 1; 41 (3): 192-195.

AbstractClinical reasoning is at the heart of physicians' competence, as it allows them to make diagnoses. However, diagnostic errors are common, due to the existence of reasoning biases. Artificial intelligence is undergoing unprecedented development in this context. It is increasingly seen as a solution to improve the diagnostic performance of physicians, or even to perform this task for them, in a totally autonomous and more efficient way. In order to understand the challenges associated with the development of artificial intelligence, it is important to understand how the machine works to make diagnoses, what are the similarities and differences with the physician's diagnostic reasoning, and what are the consequences for medical training and practice.Copyright © 2020 Société Nationale Française de Médecine Interne (SNFMI). Published by Elsevier Masson SAS. All rights reserved.

32 keywords...

hide…