Nagy Matthew, Radakovich Nathan, Nazha Aziz
Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, USA.
Center for Clinical Artificial Intelligence, Cleveland Clinic, Cleveland, USA.
Med Sci Educ. 2022 Jan 24;32(2):529-532. doi: 10.1007/s40670-022-01502-3. eCollection 2022 Apr.
The rapid development of machine learning (ML) applications in healthcare promises to transform the landscape of healthcare. In order for ML advancements to be effectively utilized in clinical care, it is necessary for the medical workforce to be prepared to handle these changes. As physicians in training are exposed to a wide breadth of clinical tools during medical school, this offers an ideal opportunity to introduce ML concepts. A foundational understanding of ML will not only be practically useful for clinicians, but will also address ethical concerns for clinical decision making. While select medical schools have made effort to integrate ML didactics and practice into their curriculum, we argue that foundational ML principles should be taught broadly to medical students across the country.
机器学习（ML）在医疗保健领域的快速发展有望改变医疗保健的格局。为了使ML的进步能在临床护理中得到有效利用，医疗人员有必要做好应对这些变化的准备。由于接受培训的医生在医学院学习期间接触到广泛的临床工具，这为引入ML概念提供了理想的机会。对ML的基本理解不仅对临床医生具有实际用途，还将解决临床决策中的伦理问题。虽然一些医学院已努力将ML教学与实践纳入其课程，但我们认为ML的基本原理应在全国范围内广泛传授给医学生。
