郭瓦迪斯,人工智能授权的医生?
Gary Takahashi1, Laurentius von Liechti1, Ebrahim Tarshizi1
1Shiley-Marcos School of Engineering, University of San Diego, 5998 Alcalá Park, San Diego, CA, 92110, United States, 1 503 847 3079.
JMIR medical education
|August 15, 2025
概括
医生越来越多地在医疗保健中使用人工智能 (AI),影响他们的角色和生产力. 将AI整合到医学教育中对于了解其潜力和挑战至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床工作流的优化 临床工作流优化
背景情况:
- 随着医生转向雇员身份和强制性电子健康记录 (EHR) 集成,医生的专业自主性下降了.
- 大型语言模型 (LLM) 和生成AI的引入在临床实践中带来了新的机遇和挑战.
研究的目的:
- 探索生成AI对临床实践和医生角色的影响.
- 倡导人工智能系统地整合到医学教育中.
主要方法:
- 在医疗保健环境中采用人工智能的当前趋势的审查.
- 分析生成性AI对临床效率,诊断精度和医生生产力的潜在影响.
- 考虑与AI实施相关的新出现的责任问题.
主要成果:
- 生成型人工智能为提高临床效率和诊断精度提供了潜力.
- 人工智能采用正在重塑医生角色,生产力预期,并引入新的责任问题.
- 在AI整合的早期阶段,医生和利益相关者的意见至关重要.
结论:
- 人工智能是一种复杂的临床工具,需要全面理解.
- 建议将人工智能系统地纳入医学课程,以准备未来的医生.
- 积极参与人工智能开发和整合是必要的,以利用其在医疗保健中的变革潜力.
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