Pelaccia T, Forestier G, Wemmert C
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.
Irimas, université de Haute-Alsace, 6, rue des Frères-Lumière, 68350 Mulhouse, France.
Rev Med Interne. 2020 Mar;41(3):192-195. doi: 10.1016/j.revmed.2019.12.014. Epub 2020 Jan 25.
Clinical 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.
临床推理是医生能力的核心，因为它使医生能够做出诊断。然而，由于存在推理偏差，诊断错误很常见。在这种背景下，人工智能正在经历前所未有的发展。它越来越被视为一种提高医生诊断性能的解决方案，甚至以一种完全自主且更高效的方式为他们执行这项任务。为了理解与人工智能发展相关的挑战，重要的是要了解机器如何进行诊断，它与医生的诊断推理有哪些异同，以及对医学培训和实践有哪些影响。
