Shah Rishi M, Shah Kavya M, Bahar Piroz, James Cornelius A
Department of Applied Mathematics, Yale College, New Haven, CT USA.
Department of Clinical Neurosciences, University of Cambridge, Hills Road, Cambridge, England CB2 0QQ UK.
Med Sci Educ. 2024 Aug 13;34(6):1565-1570. doi: 10.1007/s40670-024-02137-2. eCollection 2024 Dec.
The recent excitement surrounding artificial intelligence (AI) in health care underscores the importance of physician engagement with new technologies. Future clinicians must develop a strong understanding of data science (DS) to further enhance patient care. However, DS remains largely absent from medical school curricula, even though it is recognized as vital by medical students and residents alike. Here, we evaluate the current DS landscape in medical education and illustrate its impact in medicine through examples in pathology classification and sepsis detection. We also explore reasons for the exclusion of DS and propose solutions to integrate it into existing medical education frameworks.
近期医疗保健领域围绕人工智能（AI）的热潮凸显了医生参与新技术的重要性。未来的临床医生必须深入理解数据科学（DS），以进一步提升患者护理水平。然而，尽管医学生和住院医师都认识到数据科学至关重要，但医学院课程中却基本没有涉及这一领域。在此，我们评估了医学教育中数据科学的现状，并通过病理学分类和脓毒症检测的实例来说明其在医学中的影响。我们还探究了数据科学被排除在外的原因，并提出将其纳入现有医学教育框架的解决方案。
