人工智能在生殖尿路病理学中的应用
Ankush U Patel1, Anil V Parwani1, Swati Satturwar1
1The Ohio State University, Wexner Medical Center and James Cancer Center, Columbus, OH, USA.
Histopathology
|December 12, 2025
概括
人工智能 (AI) 在生殖尿路 (GU) 病理学中提供了显著的时间节约和ROI. 人工智能算法与癌症检测和分级的专家准确度相匹配,并提供了安全实施的框架.
科学领域:
- 数字病理学数字病理学
- 计算病理学计算病理学
- 生殖尿路 (GU) 病理学
背景情况:
- 人工智能 (AI) 是经过验证的生殖尿路病理学的工具,可以显著节省时间和带来财务回报.
- 当前的人工智能算法在前列腺,膀,脏和丸系统中检测,分级和预测癌症方面达到专家级准确度.
- 在广泛的全幻灯片图像数据集上训练的基础模型现在可以与专门的器官特定AI工具相提并论.
研究的目的:
- 为在GU病理学中安全有效地采用AI提供实际指导.
- 提出两个路线图,VALIDATED和ORCHESTRATE,这些路线图来自现实世界的部署和试点研究.
- 解决缺少普遍编的监管门和详细的实施指南AI在病理学.
主要方法:
- 从真实世界的人工智能部署和GU病理学试点研究中提炼见解.
- 开发人工智能治理和安全监督的九步VALIDATED框架.
- 创建11个原则的ORCHESTRATE蓝图,用于日常AI实施.
主要成果:
- 采用人工智能可以节省高达65%的时间,并使投资回报数百万美元.
- 人工智能算法在癌症检测,分级和预后方面表现出与专家病理学家相等或更高的准确性.
- 到2030年,人工智能预计将自动化大约80%的常规量化任务,帮助解决劳动力短缺问题并减少变化.
结论:
- 在GU病理学中成功采用人工智能需要强大的治理和实际实施策略.
- 验证-管弦乐器途径使机构能够在五年内实现效率提升,诊断卓越和积极的投资回报率.
- 人工智能集成准备通过自动化任务和赋予病理学家作为诊断编排者的权力来改变GU病理学.
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