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Updated: Jan 28, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
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机器学习在生物标志物驱动精确瘤学:自动化免疫组织化学评分和新兴方向在生殖尿道癌症

Matthew Yap1, Ioana-Maria Mihai1,2, Gang Wang1,2

  • 1Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 1Z7, Canada.

Current oncology (Toronto, Ont.)
|January 27, 2026
PubMed
概括

机器学习 (ML) 提高了生殖泌尿瘤学 (GU) 中的免疫组织化学 (IHC) 评分,提高了已有的生物标志物的一致性,并帮助发现了新的预后和预测标志物.

关键词:
人工智能的人工智能是人工智能.自动化自动化自动化自动化生物标志物生物标志物数字病理学数字病理学免疫组织化学 免疫组织化学机器学习是机器学习.精确瘤学 精确瘤学预测性 预测性 预测性预后预测预测的预测.

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