Almarzouki Abeer F, Alem Alwaleed, Shrourou Faris, Kaki Suhail, Khushi Mohammed, Mutawakkil Abdulrahman, Bamabad Motasem, Fakharani Nawaf, Alshehri Mohammed, Binibrahim Mohanad
Clinical Physiology Department, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
BMC Med Educ. 2025 Jan 30;25(1):150. doi: 10.1186/s12909-024-06446-3.
Although artificial intelligence (AI) has gained increasing attention for its potential future impact on clinical practice, medical education has struggled to stay ahead of the developing technology. The question of whether medical education is fully preparing trainees to adapt to potential changes from AI technology in clinical practice remains unanswered, and the influence of AI on medical students' career preferences remains unclear. Understanding the gap between students' interest in and knowledge of AI may help inform the medical curriculum structure.
A total of 354 medical students were surveyed to investigate their knowledge of, exposure to, and interest in the role of AI in health care. Students were questioned about the anticipated impact of AI on medical specialties and their career preferences.
Most students (65%) were interested in the role of AI in medicine, but only 23% had received formal education in AI based on reliable scientific resources. Despite their interest and willingness to learn, only 20.1% of students reported that their school offered resources enabling them to explore the use of AI in medicine. They relied mainly on informal information sources, including social media, and few students understood fundamental AI concepts or could cite clinically relevant AI research. Students who cited more scientific primary sources (rather than online media) exhibited significantly higher self-reported understanding of AI concepts in the context of medicine. Interestingly, students who had received more exposure to AI courses reported higher levels of skepticism regarding AI and were less eager to learn more about it. Radiology and pathology were perceived to be the fields most strongly affected by AI. Students reported that their overall choice of specialty was not impacted by AI.
Formal AI education seems inadequate despite students' enthusiasm concerning the application of such technology in clinical practice. Medical curricula should evolve to promote structured, evidence-based AI literacy to enable students to understand the potential applications of AI in health care.
尽管人工智能（AI）因其未来对临床实践的潜在影响而受到越来越多的关注，但医学教育一直在努力跟上技术发展的步伐。医学教育是否正在充分培养学员以适应临床实践中人工智能技术可能带来的变化这一问题仍未得到解答，而且人工智能对医学生职业偏好的影响也尚不清楚。了解学生在人工智能方面的兴趣与知识之间的差距，可能有助于为医学课程结构提供参考。
共对354名医学生进行了调查，以了解他们对人工智能在医疗保健中的作用的知识、接触情况和兴趣。学生们被问及人工智能对医学专业的预期影响以及他们的职业偏好。
大多数学生（65%）对人工智能在医学中的作用感兴趣，但只有23%的学生接受过基于可靠科学资源的人工智能正规教育。尽管他们有兴趣并愿意学习，但只有20.1%的学生表示他们的学校提供了资源，使他们能够探索人工智能在医学中的应用。他们主要依赖包括社交媒体在内的非正式信息来源，很少有学生理解人工智能的基本概念，也很少有人能引用临床相关的人工智能研究。引用更多科学原始资料（而非网络媒体）的学生在医学背景下对人工智能概念的自我报告理解水平显著更高。有趣的是，接触人工智能课程更多的学生对人工智能的怀疑程度更高，也不太渴望进一步了解它。放射学和病理学被认为是受人工智能影响最大的领域。学生们表示，他们对专业的总体选择不受人工智能影响。
尽管学生们对这种技术在临床实践中的应用充满热情，但正规的人工智能教育似乎并不充分。医学课程应不断发展，以促进结构化的、基于证据的人工智能素养，使学生能够理解人工智能在医疗保健中的潜在应用。
