人工智能作为医疗器械在监管数据库中的不良事件报告:系统审查协议
Aditya U Kale1,2,3,4, Riya Dattani5, Ashley Tabansi6
1Institute of Inflammation and Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom.
JMIR research protocols
|July 11, 2024
概括
本研究回顾了三个监管数据库中对人工智能作为医疗器械 (AIaMD) 报告的不良事件. 它旨在通过识别报告差距和描述事件类型来改善AIaMD安全监测.
科学领域:
- 医疗器械安全 医疗器械安全
- 医疗保健中的人工智能
- 监管科学是一种监管科学.
背景情况:
- 由于识别,知识和文化障碍,医疗器械的不良事件 (AE) 报告不足.
- 人工智能作为医疗设备 (AIaMD) 引入了算法偏差等独特风险,需要强有力的安全监测.
- 目前的AE报告系统在检测,归因和报告AIaMD安全信号方面存在局限性.
研究的目的:
- 在主要监管数据库中对AIaMD报告的不良事件 (AE) 进行系统审查和描述.
- 确定与AIaMD相关的AE的频率和类型.
- 了解当前AE报告AIaMD的局限性,并为未来的安全监测策略提供信息.
主要方法:
- 从美国,英国和澳大利亚公开访问的AE数据库的系统审查.
- 纳入标准:涉及人工智能医疗设备的AE报告;排除:软件作为没有AI的医疗设备.
- 数据提取和描述性分析以根据监管指南来描述AE类型,频率和严重程度.
主要成果:
- 范围搜索已经完成,选将于2024年4月开始,数据提取/合成将于2024年5月至8月进行.
- 审查将突出AIaMD报告的AE类型,并确定报告漏洞.
- 预期发现:与AIaMD相关的间接伤害报告率特别低.
结论:
- 这次系统审查是首次分析来自三个监管来源的AIaMD的AE报告.
- 该研究将提供AIaMD安全性的现实证据,但承认由于数据库不透明而存在的局限性.
- 调查结果将有助于监管机构和政策制定者加强AIaMD安全监测流程.
关键词:
不良事件是不良事件.人工智能的人工智能是人工智能.人工智能 卫生技术 技术 人工智能描述性分析 描述性分析有关反的意见反反反.医疗保健产品 医疗保健产品医疗器械 医疗器械 医疗器械监管数据库是监管数据库.监管科学是一种监管科学.报告系统报告系统有风险的风险是有风险的风险.在安全方面,安全是安全的.安全问题安全问题.安全监控安全监控安全监控更多相关视频
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