在数字病理学中弥合临床计算透明度差距
Qiangqiang Gu1, Ankush Patel1, Matthew G Hanna2
1From the Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota (Gu, Patel, Garcia, Zarella, McClintock, Hart).
Archives of pathology & laboratory medicine
|June 13, 2024
概括
弥合病理学家和开发人员之间的差距是计算病理学的关键. 对计算方法和临床需求的更好理解将改善计算机辅助诊断 (CAD) 工具和患者护理.
科学领域:
- 计算病理学计算病理学
- 医疗信息学医学信息学
- 数字病理学数字病理学
背景情况:
- 计算病理学将计算分析与临床病理学相结合,以提高诊断和生产力.
- 病理学家和开发人员之间的沟通障碍阻碍了计算病理学工具的全部潜力.
- 现有的计算机辅助诊断 (CAD) 工具显示出希望,其中一些获得了监管部门的批准.
研究的目的:
- 提出一个标准化的框架,以改善病理学家和开发人员之间的相互理解.
- 加强计算机辅助诊断 (CAD) 工具的开发和临床应用.
- 促进对临床目标和计算方法的更好理解.
主要方法:
- 定义病理学家和计算机科学家在CAD开发生命周期中的关键角色.
- 倡导病理学家了解计算术语,过程和限制.
- 鼓励计算机科学家理解临床用例,避免临床上无关紧要的指标.
主要成果:
- 病理学家对机器学习模型的更好理解对于防止滥用和误解至关重要.
- 与病理学家基准相比,需要对算法更准确的性能表示.
- 解决沟通缺口可以导致更有效的CAD工具开发和实施.
结论:
- 对计算和临床范式的全面掌握对于弥合计算病理学的翻译差距至关重要.
- 学科之间的相互理解将提高疾病诊断的准确性和效率.
- 通过先进的诊断能力,改进的协作最终有利于患者护理.
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