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通过建立当地能力来消除人工智能数字沟.

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科学领域:

  • 医疗信息学 医疗信息学
  • 医疗保健中的人工智能
  • 健康 公平 卫生 公平

背景情况:

  • 提供卫生服务的组织 (HDO) 越来越多地采用人工智能 (AI) 工具来改善临床和运营.
  • 在学术医疗中心和资源较低的环境之间,人工智能采用能力存在显著差异.
  • 这种资源差距阻碍了公平获得人工智能的好处,影响了患者护理和运营效率.

研究的目的:

  • 为了识别HDOs在AI产品生命周期管理能力中日益增长的差距.
  • 提出一个可扩展的解决方案,在不同的医疗保健环境中公平地采用人工智能.
  • 倡导有针对性的公共投资,以支持全国人工智能能力建设.

主要方法:

  • 对人工智能采用趋势和HDO资源差异的分析.
  • 检查历史技术采用模式 (EHR,远程医疗) 和政府反应.
  • 建议和评估技术,监管和法律支持的枢纽网络模型.

主要成果:

  • 人工智能产品生命周期管理所需的资源和能力存在重大差距.
  • 之前的政府干预,如卓越中心,成功地解决了收养差异.
  • 一个集线网络模型在为HDOs提供基本支持服务方面显示出希望.

结论:

  • 人工智能在医疗保健中的广泛和有意义的采用需要解决资源和能力差距.
  • 通过公共投资支持的枢纽和分支网络可以促进公平的AI实施.
  • 所有健康人工智能生态系统利益相关者之间的协调对于安全有效的人工智能部署至关重要.