超越监管合规:评估放射学人工智能应用在部署中的应用
J Ross1, S Hammouche1, Y Chen2
1Department of Cancer and Surgery, Imperial College London, UK.
Clinical radiology
|February 15, 2024
概括
在医疗保健中实施人工智能 (AI) 面临信任和安全挑战. 这项研究提出了超出监管批准的增强验证,以建立专业信心并防止患者受到伤害.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床治理的管理.
背景情况:
- 对人工智能应用程序的监管批准并不完全解决可靠性,问责制,安全性和治理等实际问题.
- 缺乏专业的信心和对增强验证的感知需求阻碍了AI在常规临床实践中的采用.
- 对于新型和相对未经测试的人工智能技术,现有的验证和合规措施可能不足.
研究的目的:
- 提出一种超越标准监管合规性的人工智能 (AI) 应用程序验证方法.
- 加强信任并防止与医疗保健环境中人工智能实施相关的伤害.
- 为在实验室和临床实践中严格评估AI工具提供框架.
主要方法:
- 在实验室环境中对人工智能应用进行独立的基准测试.
- 在现实实践中对人工智能应用进行临床审计.
- 实施超出基准监管要求的验证策略.
主要成果:
- 拟议的方法旨在提高专业人士对人工智能技术的信心.
- 预计增强的验证方法将提高AI工具的安全性和可靠性.
- 该战略重点是通过全面评估来预防伤害.
结论:
- 标准监管合规性不足以确保AI在医疗保健中的安全和有效实施.
- 独立的基准测试和临床审计对于建立对AI应用程序的信任至关重要.
- 需要采取积极的验证方法,以克服人工智能采用障碍,并确保患者安全.
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