验证和评估是确保安全的人工智能健康应用的关键
Michael Rigby1, Elisavet Andrikopoulou2, Mirela Prgomet3
1Keele University, School of Social, Political and Global Studies and School of Primary, Community and Social Care, Keele, United Kingdom.
Studies in health technology and informatics
|October 3, 2025
概括
医疗信息学中的人工智能 (AI) 需要严格的科学验证和安全测试. 建立强大的评估原则至关重要,以减轻诸如偏见之类的风险,并确保可靠的健康AI部署.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 医疗技术评估 医疗技术评估
背景情况:
- 人工智能 (AI) 正在健康信息学领域迅速发展.
- 目前的人工智能验证缺乏其他健康技术的严格性.
- 健康人工智能可以引入和延续偏见,造成安全和效率风险.
研究的目的:
- 重新审视人工智能评估的健康信息学原则.
- 建立人工智能证据生产的科学原则.
- 解决对健康AI严格验证的需求.
主要方法:
- 审查现有的健康信息学原则和技术.
- 对人工智能评估的预防原则的应用.
- 整合持续质量改进方法.
主要成果:
- 需要来自AI开发人员的强有力的证据和评估轨迹.
- 呼吁决策者要求严格对人工智能进行评估.
- 重点在于平衡敏捷评估与彻底性.
结论:
- 健康AI评估需要科学原则.
- 敏捷和务实的方法对于不断发展的人工智能至关重要.
- 持续评估是防止错误和偏见的延续的关键.
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