Quantitative Assessment of Tumor-Infiltrating Lymphocytes Using Machine Learning Predicts Survival in Muscle-Invasive Bladder Cancer

Quantitative Assessment of Tumor-Infiltrating Lymphocytes Using Machine Learning Predicts Survival in Muscle-Invasive Bladder Cancer

(1) Purpose: Although assessment of tumor-infiltrating lymphocytes (TILs) has been acknowledged to have important predictive prognostic value in muscle-invasive bladder cancer (MIBC), it is limited by inter- and intra-observer variability, hampering widespread clinical application. We aimed to evalu...

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Bibliographic Details
Main Authors: Qingyuan Zheng, Rui Yang, Xinmiao Ni, Song Yang, Panpan Jiao, Jiejun Wu, Lin Xiong, Jingsong Wang, Jun Jian, Zhengyu Jiang, Lei Wang, Zhiyuan Chen, Xiuheng Liu
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Journal of Clinical Medicine
Subjects:
tumor-infiltrating lymphocytes
whole-slide image
machine learning
prognostic marker
muscle-invasive bladder cancer
Online Access:https://www.mdpi.com/2077-0383/11/23/7081

Internet

https://www.mdpi.com/2077-0383/11/23/7081

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