Burwell Julian Michael
Department of Medical Education, Geisinger Commonwealth School of Medicine, Scranton, PA, United States of America.
J Med Syst. 2025 Jun 11;49(1):79. doi: 10.1007/s10916-025-02214-y.
Machine learning should be integrated into medical curricula to prepare physicians-in-training for 21st-century practice conditions. This comment proposes practical implementation strategies that build upon existing educational frameworks by drawing parallels to traditional statistical methods. By incorporating these skills through a phased approach, medical education can fulfill its duty to the public by preparing future physicians to effectively evaluate emergent technology, identify potential sources of bias, and better serve patients.
机器学习应融入医学课程，以便让正在接受培训的医生为21世纪的执业环境做好准备。本评论提出了切实可行的实施策略，这些策略借鉴传统统计方法，以现有的教育框架为基础。通过分阶段的方式融入这些技能，医学教育可以履行其对公众的责任，培养未来的医生有效地评估新兴技术、识别潜在的偏差来源并更好地服务患者。
