Li Wei, Shi Hai-Yan, Chen Xiao-Ling, Lan Jian-Zeng, Rehman Attiq-Ur, Ge Meng-Wei, Shen Lu-Ting, Hu Fei-Hong, Jia Yi-Jie, Li Xiao-Min, Chen Hong-Lin
School of Nursing and Rehabilitation, Nantong University, Nantong, Jiangsu, China.
Nantong University Affiliated Rugao Hospital, Rugao People's Hospital, Nantong, Jiangsu, China.
Med Teach. 2024 Oct 31:1-14. doi: 10.1080/0142159X.2024.2418936.
With the advancement of Artificial Intelligence (AI), it has had a profound impact on medical education. Understanding the advantages and issues of AI in medical education, providing guidance for educators, and overcoming challenges in the implementation process is particularly important. The objective of this study is to explore the current state of AI applications in medical education. A systematic search was conducted across databases such as PsycINFO, CINAHL, Scopus, PubMed, and Web of Science to identify relevant studies. The Critical Appraisal Skills Programme (CASP) was employed for the quality assessment of these studies, followed by thematic synthesis to analyze the themes from the included research. Ultimately, 21 studies were identified, establishing four themes: (1) Shaping the Future: Current Trends in AI within Medical Education; (2) Advancing Medical Instruction: The Transformative Power of AI; (3) Navigating the Ethical Landscape of AI in Medical Education; (4) Fostering Synergy: Integrating Artificial Intelligence in Medical Curriculum. Artificial intelligence's role in medical education, while not yet extensive, is impactful and promising. Despite challenges, including ethical concerns over privacy, responsibility, and humanistic care, future efforts should focus on integrating AI through targeted courses to improve educational quality.
随着人工智能（AI）的发展，它对医学教育产生了深远影响。了解人工智能在医学教育中的优势和问题，为教育工作者提供指导，并克服实施过程中的挑战尤为重要。本研究的目的是探讨人工智能在医学教育中的应用现状。我们在PsycINFO、CINAHL、Scopus、PubMed和Web of Science等数据库中进行了系统检索，以识别相关研究。采用批判性评估技能计划（CASP）对这些研究进行质量评估，随后进行主题综合分析，以分析纳入研究中的主题。最终，确定了21项研究，确立了四个主题：（1）塑造未来：医学教育中人工智能的当前趋势；（2）推进医学教学：人工智能的变革力量；（3）应对医学教育中人工智能的伦理格局；（4）促进协同：将人工智能融入医学课程。人工智能在医学教育中的作用虽然尚未广泛，但具有影响力且前景广阔。尽管存在挑战，包括对隐私、责任和人文关怀的伦理担忧，但未来的努力应集中在通过有针对性的课程整合人工智能，以提高教育质量。
