人工智能时代的计算病理学 - - 拥抱而不是害怕
Alfonso Tan-Garcia1, Tzy Harn Chua1, Wei-Qiang Leow1,2,3
1Department of Anatomical Pathology, Singapore General Hospital, Singapore.
The journal of pathology. Clinical research
|September 22, 2025
概括
数字病理学和人工智能 (AI) 正在改变癌症诊断. 集成到数字病理学工作流程中的AI模型显示出预测各种癌症患者生存率和治疗反应的前景.
科学领域:
- 组织病理学 组织病理学
- 数字病理学数字病理学
- 计算病理学计算病理学
- 人工智能的人工智能
背景情况:
- 传统的解剖病理学依赖于手工显微镜幻灯片的解释.
- 数字病理学 (DP) 能够实现整个幻灯片成像,促进新的应用.
- DP刺激了计算病理学,将AI集成到高级分析中.
研究的目的:
- 审查最近的研究应用AI在临床应用数字病理学.
- 突出AI在预测生存和治疗反应方面的作用.
- 讨论AI在病理学中的潜力和挑战.
主要方法:
- 在数字病理学管道中使用人工智能模型的研究审查.
- 人工智能的应用用于组织形态学量化.
- 用于诊断,预测和预后目的的AI模型.
主要成果:
- 人工智能模型用于预测胃癌,乳腺癌和扩散大B细胞淋巴瘤的生存率和治疗反应.
- 在DP中展示各种AI整合方法.
- 有潜力提高诊断准确度,个性化治疗和简化工作流程.
结论:
- 数字病理学的AI为临床应用提供了巨大的潜力.
- 需要进一步的研究来应对准确性,成本和道德等挑战.
- 病理学家对人工智能在现场采用方面表现出谨慎的乐观.
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