在安大略省建立一个人工智能沙箱用于诊断成像
Michael Bravo1, Marwan G Althagafi1, Anastasia Kalantarova1
1Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
Studies in health technology and informatics
|February 13, 2026
概括
安大略省提出了一个新的用于诊断成像的AI沙箱,以应对分散的AI采用挑战. 这一举措确保了人工智能工具的安全评估和扩展,促进了全省可信的创新.
科学领域:
- 医疗成像医学成像
- 医疗保健中的人工智能
- 卫生政策 卫生政策
背景情况:
- 安大略省在诊断成像 (DI) 实施方面面临重大挑战,特别是人工智能 (AI) 解决方案的零碎采用.
- 加拿大放射科医生协会 (CAR) 强调需要在临床部署之前为AI工具评估提供可访问的,模式特定的沙箱.
研究的目的:
- 在安大略省提出一个由省级管理的AI沙箱用于诊断成像.
- 建立一个安全的环境来测试,验证和扩展DI中的AI创新.
- 通过设计时的隐私框架来确保负责任的AI采用.
主要方法:
- 开发一个用于诊断成像的省级AI沙盒框架.
- 整合六个关键政策领域:临床效用,伦理和隐私,技术设计,治理,法律合规和可持续性.
- 利用安大略省卫生部对可靠人工智能的承诺.
主要成果:
- 一个拟议的AI沙箱模型,旨在安全测试和验证诊断成像中的AI工具.
- 一个全面的框架,整合多个政策领域,以指导负责任的AI实施.
- 一条促进安大略省诊断成像部门公平,透明和全系统创新的途径.
结论:
- 拟议的AI沙盒提供了一种结构化的方法,以克服安大略省诊断成像中AI采用方面的挑战.
- 该倡议支持将人工智能技术安全,道德和有效地整合到临床实践中.
- 该框架旨在推动全省医疗保健系统的可靠和可持续的人工智能创新.
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