展示你的工作:在医疗保健中负责任的模型报告 人工智能
Muhammad Aurangzeb Ahmad1, Carly Marie Eckert2
1University of Washington, Seattle; Department of Computer Science & Software Engineering, University of Washington Bothell. Electronic address: https://twitter.com/vonaurum.
The Surgical clinics of North America
|June 17, 2023
概括
医疗保健中的标准化模型报告对于机器学习部署至关重要. 它确保了透明度,公平性和通用性,解决了AI在医学中的关键问题.
科学领域:
- 医疗信息学 医疗信息学
- 机器学习 机器学习
- 医疗保健中的人工智能
背景情况:
- 标准化模型报告对于在医疗保健中开发和部署机器学习 (ML) 模型至关重要.
- 有效的报告包括共享绩效指标和元数据,以进行可靠的模型评估.
- 解决可解释性,透明度,公平性和可概括性等问题对于医疗保健中的AI至关重要.
研究的目的:
- 强调在医疗保健机器学习生命周期中标准化和全面的模型报告的重要性.
- 突出全面报告如何促进信任和负责任的AI部署.
- 强调医生参与在确保临床相关性和安全性方面的作用.
主要方法:
- 审查机器学习模型报告的最佳实践.
- 分析全面模型报告的组件,包括绩效指标和元数据.
- 讨论在整个模型开发生命周期中整合负责任的报告.
主要成果:
- 标准化报告通过提供必要的背景来增强模型评估.
- 彻底的报告直接解决了关于医疗保健中的AI的关键问题.
- 通过报告进行公开沟通,支持利益相关者的理解和信任.
- 医生的参与确保了临床有效性,并减轻了潜在的负面后果.
结论:
- 负责任的模型报告是成功和道德部署机器学习在医疗保健中不可或缺的一部分.
- 综合报告促进了透明度,公平性和通用性,建立了对人工智能医疗保健解决方案的信心.
- 涉及临床医生的协作开发是将AI模型与患者护理需求保持一致的关键.
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