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相关实验视频

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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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它是否有效,有助于,并留下来? 在放射学中实施人工智能工具的框架.

Chintan Shah1, Satyam Ghodasara2, David Chen3

  • 1Medical Director-Imaging AI, Staff, Section of Neuroradiology and Section of Imaging Informatics, Diagnostics Institute-Imaging, Cleveland Clinic, Cleveland, Ohio.

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概括

在放射学中实施人工智能 (AI) 需要一个结构化的框架. 这种四阶段的方法确保人工智能工具得到验证,负责任地部署,评估价值,并持续监测安全性和性能.

关键词:
人工智能实施实施AI实施人工智能的人工智能是人工智能.绩效监测 绩效监测 绩效监测 绩效监测 绩效监测 绩效监测 绩效监测验证验证的时间价值的价值的价值是一个价值.

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科学领域:

  • 放射学 放射学是一门学科.
  • 医疗成像医学成像
  • 医疗保健中的人工智能

背景情况:

  • 人工智能 (AI) 在临床放射学中的采用正在增加.
  • 为了有效和负责任地实施人工智能,需要采用结构化的方法.
  • 目前的实施策略往往缺乏全面的治理.

研究的目的:

  • 提出一个实际的,四个阶段的框架,用于在临床放射学中负责任地实施AI.
  • 通过将AI工具集成到放射学工作流程的过程指导医疗保健提供者.
  • 解决有关人工智能的有效性,临床实用性和长期性能的关键问题.

主要方法:

  • 拟议的框架包括四个阶段:验证,部署,价值评估和部署后监督.
  • 验证涉及对本地数据进行追溯测试,以评估模型性能.
  • 部署包括试验和全面实施阶段,重点是工作流集成和利益相关者的反.
  • 价值评估追踪财务和非财务回报,而监控监控数据漂移并保持AI安全.

主要成果:

  • 该框架为人工智能实施提供了以治理为导向的途径.
  • 它系统地解决了人工智能工具是否有效,提供了临床益处,并随着时间的推移保持有效.
  • 成功实施取决于严格的验证,谨慎的部署,持续的价值评估和持续的监督.

结论:

  • 结构化,分阶段的框架对于成功和负责任地在放射学中采用AI至关重要.
  • 这种以治理为导向的方法可以确保人工智能工具得到验证,在临床上有用,并安全用于长期使用.
  • 拟议的框架促进了人工智能的整合,最大限度地提高了它的好处,同时降低了临床实践中的风险.