Development and validation of a deep learning-based pathomics signature for prognosis and chemotherapy benefits in colorectal cancer: a retrospective multicenter cohort study

Development and validation of a deep learning-based pathomics signature for prognosis and chemotherapy benefits in colorectal cancer: a retrospective multicenter cohort study

IntroductionThe conventional tumor-node-metastasis (TNM) classification system remains limited in accurately forecasting prognosis and guiding adjuvant chemotherapy decisions for patients with colorectal cancer (CRC). To address this gap, we introduced and validated a novel pathomics signature (PSCR...

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Main Authors: Shenghan Lou, Yanming Huang, Fenqi Du, Jingmin Xue, Genshen Mo, Hao Li, Zhanjiang Yu, Yuanchun Li, Hang Wang, Yuze Huang, Haonan Xie, Wenjie Song, Xinyue Zhang, Huiying Li, Chun Lou, Peng Han
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Immunology
Subjects:
colorectal cancer
deep learning
whole slide image
pathology
prognosis
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2025.1602909/full
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https://www.frontiersin.org/articles/10.3389/fimmu.2025.1602909/full

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