从代理人到治理:在大型语言模型时代,临床医生的基本人工智能技能
Weiping Cao1,2, Qing Zhang1, Jialin Liu3,4
1Department of Cardiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Journal of medical Internet research
|January 14, 2026
概括
临床医生需要在医疗保健中获得人工智能 (AI) 的新技能. 一个三层框架指导安全和负责任的AI使用,从基本的提示工程到先进的道德治理,改善患者护理.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 临床实践 临床实践
背景情况:
- 大型语言模型 (LLM) 越来越多地集成到临床环境中.
- 临床医生迫切需要培养负责任的人工智能使用能力.
- 将人工智能机会与问责制相平衡,对于患者安全至关重要.
研究的目的:
- 为使用人工智能的临床医生提出一个三层能力框架.
- 引导临床医生的演变,从人工智能用户到负责任的人工智能管理员.
- 加强安全有效的AI整合到医疗保健中.
主要方法:
- 制定一个三层能力框架:基础,中级和高级技能.
- 一级专注于安全使用:快速工程,人 - 人工智能交互,隐私和同意.
- 第二层强调评估:偏差检测,可解释性和工作流集成.
- 第三层涉及领导力:道德治理,监管战略和模式管理.
主要成果:
- 该框架概述了每个级别的特定能力,从基本到高级AI管理层的进展.
- 能力包括快速工程,偏见检测,道德治理和模型生命周期管理.
- 建议将其纳入医学教育和职位描述.
结论:
- 拟议的框架支持临床医生安全和负责任地使用人工智能工具.
- 通过该框架部署标准化的AI可以增强临床实践.
- 有效的AI整合有可能改善患者的治疗结果和安全.
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