Singla Rohit, Pupic Nikola, Ghaffarizadeh Seyed-Aryan, Kim Caroline, Hu Ricky, Forster Bruce B, Hacihaliloglu Ilker
MD/PhD Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.
NPJ Digit Med. 2024 Nov 18;7(1):323. doi: 10.1038/s41746-024-01307-1.
The integration of artificial intelligence (AI) education into medical curricula is critical for preparing future healthcare professionals. This research employed the Delphi method to establish an expert-based AI curriculum for Canadian undergraduate medical students. A panel of 18 experts in health and AI across Canada participated in three rounds of surveys to determine essential AI learning competencies. The study identified key curricular components across ethics, law, theory, application, communication, collaboration, and quality improvement. The findings demonstrate substantial support among medical educators and professionals for the inclusion of comprehensive AI education, with 82 out of 107 curricular competencies being deemed essential to address both clinical and educational priorities. It additionally provides suggestions on methods to integrate these competencies within existing dense medical curricula. The endorsed set of objectives aims to enhance AI literacy and application skills among medical students, equipping them to effectively utilize AI technologies in future healthcare settings.
将人工智能（AI）教育融入医学课程对于培养未来的医疗保健专业人员至关重要。本研究采用德尔菲法为加拿大本科医学生建立了一个基于专家意见的AI课程。来自加拿大各地的18位健康与AI领域的专家组成的小组参与了三轮调查，以确定AI学习的基本能力。该研究确定了涵盖伦理、法律、理论、应用、沟通、协作和质量改进等方面的关键课程组成部分。研究结果表明，医学教育工作者和专业人员大力支持纳入全面的AI教育，107项课程能力中有82项被认为对于解决临床和教育重点至关重要。此外，它还就将这些能力整合到现有的密集医学课程中的方法提供了建议。认可的目标旨在提高医学生的AI素养和应用技能，使他们能够在未来的医疗环境中有效地利用AI技术。
