{"title":"人工智能变革医学教育的进展:全面概述。","authors":"Aliasghar Khakpaki","doi":"10.1080/10872981.2025.2542807","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) is revolutionizing medical education by introducing innovative tools and reshaping traditional teaching and learning methods. AI technologies such as virtual and augmented reality, adaptive learning platforms, and AI-driven assessments are increasingly recognized for their potential to enhance diagnostic precision, clinical decision-making, and personalized learning experiences.</p><p><strong>Objective: </strong>This narrative review explores the current trends, challenges, and innovations associated with the integration of AI in medical education. It aims to critically examine how AI transforms teaching and learning processes while addressing ethical concerns and practical barriers.</p><p><strong>Methods: </strong>We performed a systematic literature search across three major databases (PubMed, Scopus, and Web of Science) for publications dated 2010-2024. Our search strategy employed key terms including 'artificial intelligence,' 'medical education,' and 'AI-based learning platforms' to identify relevant peer-reviewed articles, review papers, and case studies. After screening and selection, 67 studies met our inclusion criteria for final analysis.</p><p><strong>Results: </strong>AII technologies improve learning outcomes by creating personalized, immersive, and interactive environments. They support clinical decision-making and procedural skills training while addressing diverse learner needs. However, ethical issues like data privacy, algorithmic biases, and equitable access, coupled with challenges like faculty resistance and technological infrastructure gaps, limit broader adoption.</p><p><strong>Conclusion: </strong>AI is an important tool in medical education, offering significant opportunities to enhance learning outcomes and bridge educational gaps. However, its successful integration requires ethical frameworks, faculty training, and equitable resource allocation. A balanced approach that combines technological innovation with human-centered pedagogy is essential to preserve empathy and ethical care in healthcare.</p>","PeriodicalId":47656,"journal":{"name":"Medical Education Online","volume":"30 1","pages":"2542807"},"PeriodicalIF":3.8000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12351741/pdf/","citationCount":"0","resultStr":"{\"title\":\"Advancements in artificial intelligence transforming medical education: a comprehensive overview.\",\"authors\":\"Aliasghar Khakpaki\",\"doi\":\"10.1080/10872981.2025.2542807\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Artificial intelligence (AI) is revolutionizing medical education by introducing innovative tools and reshaping traditional teaching and learning methods. AI technologies such as virtual and augmented reality, adaptive learning platforms, and AI-driven assessments are increasingly recognized for their potential to enhance diagnostic precision, clinical decision-making, and personalized learning experiences.</p><p><strong>Objective: </strong>This narrative review explores the current trends, challenges, and innovations associated with the integration of AI in medical education. It aims to critically examine how AI transforms teaching and learning processes while addressing ethical concerns and practical barriers.</p><p><strong>Methods: </strong>We performed a systematic literature search across three major databases (PubMed, Scopus, and Web of Science) for publications dated 2010-2024. Our search strategy employed key terms including 'artificial intelligence,' 'medical education,' and 'AI-based learning platforms' to identify relevant peer-reviewed articles, review papers, and case studies. After screening and selection, 67 studies met our inclusion criteria for final analysis.</p><p><strong>Results: </strong>AII technologies improve learning outcomes by creating personalized, immersive, and interactive environments. They support clinical decision-making and procedural skills training while addressing diverse learner needs. However, ethical issues like data privacy, algorithmic biases, and equitable access, coupled with challenges like faculty resistance and technological infrastructure gaps, limit broader adoption.</p><p><strong>Conclusion: </strong>AI is an important tool in medical education, offering significant opportunities to enhance learning outcomes and bridge educational gaps. However, its successful integration requires ethical frameworks, faculty training, and equitable resource allocation. A balanced approach that combines technological innovation with human-centered pedagogy is essential to preserve empathy and ethical care in healthcare.</p>\",\"PeriodicalId\":47656,\"journal\":{\"name\":\"Medical Education Online\",\"volume\":\"30 1\",\"pages\":\"2542807\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12351741/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medical Education Online\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/10872981.2025.2542807\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/8/12 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Education Online","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/10872981.2025.2542807","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/12 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
摘要
背景:人工智能(AI)通过引入创新工具和重塑传统的教学方法,正在彻底改变医学教育。人工智能技术,如虚拟和增强现实、自适应学习平台和人工智能驱动的评估,因其在提高诊断精度、临床决策和个性化学习体验方面的潜力而日益得到认可。目的:本综述探讨了人工智能在医学教育中整合的当前趋势、挑战和创新。它旨在批判性地研究人工智能如何改变教学过程,同时解决伦理问题和实际障碍。方法:我们在三个主要数据库(PubMed, Scopus和Web of Science)中进行了系统的文献检索,检索日期为2010-2024年的出版物。我们的搜索策略使用了包括“人工智能”、“医学教育”和“基于人工智能的学习平台”在内的关键术语来识别相关的同行评审文章、综述论文和案例研究。经过筛选和选择,67项研究符合最终分析的纳入标准。结果:ai技术通过创建个性化、沉浸式和交互式环境来改善学习效果。他们支持临床决策和程序技能培训,同时满足不同学习者的需求。然而,数据隐私、算法偏见和公平访问等道德问题,加上教师阻力和技术基础设施差距等挑战,限制了人工智能的广泛采用。结论:人工智能是医学教育的重要工具,为提高学习成果和缩小教育差距提供了重要机会。然而,它的成功整合需要道德框架、教师培训和公平的资源分配。将技术创新与以人为本的教学法相结合的平衡方法对于保持医疗保健中的同理心和道德关怀至关重要。
Advancements in artificial intelligence transforming medical education: a comprehensive overview.
Background: Artificial intelligence (AI) is revolutionizing medical education by introducing innovative tools and reshaping traditional teaching and learning methods. AI technologies such as virtual and augmented reality, adaptive learning platforms, and AI-driven assessments are increasingly recognized for their potential to enhance diagnostic precision, clinical decision-making, and personalized learning experiences.
Objective: This narrative review explores the current trends, challenges, and innovations associated with the integration of AI in medical education. It aims to critically examine how AI transforms teaching and learning processes while addressing ethical concerns and practical barriers.
Methods: We performed a systematic literature search across three major databases (PubMed, Scopus, and Web of Science) for publications dated 2010-2024. Our search strategy employed key terms including 'artificial intelligence,' 'medical education,' and 'AI-based learning platforms' to identify relevant peer-reviewed articles, review papers, and case studies. After screening and selection, 67 studies met our inclusion criteria for final analysis.
Results: AII technologies improve learning outcomes by creating personalized, immersive, and interactive environments. They support clinical decision-making and procedural skills training while addressing diverse learner needs. However, ethical issues like data privacy, algorithmic biases, and equitable access, coupled with challenges like faculty resistance and technological infrastructure gaps, limit broader adoption.
Conclusion: AI is an important tool in medical education, offering significant opportunities to enhance learning outcomes and bridge educational gaps. However, its successful integration requires ethical frameworks, faculty training, and equitable resource allocation. A balanced approach that combines technological innovation with human-centered pedagogy is essential to preserve empathy and ethical care in healthcare.
期刊介绍:
Medical Education Online is an open access journal of health care education, publishing peer-reviewed research, perspectives, reviews, and early documentation of new ideas and trends.
Medical Education Online aims to disseminate information on the education and training of physicians and other health care professionals. Manuscripts may address any aspect of health care education and training, including, but not limited to:
-Basic science education
-Clinical science education
-Residency education
-Learning theory
-Problem-based learning (PBL)
-Curriculum development
-Research design and statistics
-Measurement and evaluation
-Faculty development
-Informatics/web