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在解剖病理学中民主化人工智能

Thomas J Flotte1, Stephanie A Derauf1, Rachel K Byrd1

  • 1From the Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, Minnesota (Flotte, Derauf, Byrd, Kroneman, Bell, Hart, Garcia).

Archives of pathology & laboratory medicine
|April 22, 2024
PubMed
概括
此摘要是机器生成的。

开发了一个生态系统,以支持病理学家创建人工智能算法. 这种方法使AI在病理学中民主化,降低成本并加速采用.

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科学领域:

  • 病理学 病理学 病理学
  • 医疗信息学 医疗信息学
  • 计算机科学 计算机科学

背景情况:

  • 人工智能 (AI) 正在彻底改变解剖病理学.
  • 员工参与对于AI算法开发和实施至关重要.

研究的目的:

  • 建立一个支持生态系统,使所有专业水平的病理学家能够开发AI算法.
  • 确保人工智能工具从开发环境到生产环境的无过渡.

主要方法:

  • 由于时间和资源的限制,选择了自动售货解决方案而不是内部开发.
  • 供应商的建议被病理学,IT和安全团队评估.
  • 一个由84名研究人员组成的初始队伍接受了培训和专家支持,其中30个项目正在通过模型开发取得进展.

主要成果:

  • 一个自动售货解决方案促进了AI开发和生产管道的建立.
  • 在31个AI算法开发项目中,有30个项目成功完成了注释,培训和验证.
  • 15个项目摘要提交给国家科学会议.

结论:

  • 通过创建支持性生态系统,在病理学中实现人工智能的民主化,降低了进入障碍.
  • 这种方法可以降低人工智能算法开发的总体成本.
  • 改进的算法质量和更快的采用率是预期的结果.