一个学术观点 (2025) 整合生成人工智能在医学教育:转变学习和实践
Mohammad Almansour1, Mona Soliman1, Raniah Aldekhyyel1
1Department of Medical Education, College of Medicine, King Saud University, Riyadh, SAU.
Cureus
|April 25, 2025
概括
生成型人工智能 (GAI) 通过个性化辅导和行政效率来增强医学教育. 伦理实施对于改善医疗保健专业人员培训和患者护理至关重要.
科学领域:
- 医疗教育 技术 技术 医学教育
- 医疗保健中的人工智能
- 数字健康数字健康
背景情况:
- 生成型人工智能 (GAI) 为医学教育带来了变革的潜力.
- 传统方法在教学,评估和临床培训方面面临挑战.
- GAI提供创新解决方案,以提高学习体验和行政效率.
研究的目的:
- 探索GAI在医学教育中的当前和潜在应用.
- 评估GAI在各种教育领域的可行性和影响.
- 确定GAI可以优化学习和培训的关键领域.
主要方法:
- 采用了一个叙事审查方法.
- 在2025年1月,在PubMed,Scopus和谷歌学者中进行了结构化的文献搜索.
- 使用了专家分析,包括代头脑风暴和六位领域专家的评估.
主要成果:
- 确定了GAI应用的十个领域:质量和管理,课程开发,教学和学习,评估和评估,临床培训,学术指导,学生研究,学生事务,实习管理和学生活动.
- 通过自适应辅导和绩效仪表板,GAI促进了个性化的学习.
- 通过沉浸式模拟和虚拟患者接触,GAI增强了临床培训,并简化了研究过程.
结论:
- GAI具有显著的潜力,可以提高医疗环境中的教育质量和运营效率.
- 伦理考虑,包括数据隐私,算法偏见和公平访问,需要强大的框架和政策.
- 有针对性和以道德为导向的GAI实施可以为未来的医疗保健专业人员提供以患者为中心的护理所必需的适应性技能.
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