A Computational Tumor-Infiltrating Lymphocyte Assessment Method Comparable with Visual Reporting Guidelines for Triple-Negative Breast Cancer

A Computational Tumor-Infiltrating Lymphocyte Assessment Method Comparable with Visual Reporting Guidelines for Triple-Negative Breast Cancer

Background: Tumor-infiltrating lymphocytes (TILs) are clinically significant in triple-negative breast cancer (TNBC). Although a standardized methodology for visual TILs assessment (VTA) exists, it has several inherent limitations. We established a deep learning-based computational TIL assessment (C...

Full description

Bibliographic Details
Main Authors: Peng Sun, Jiehua He, Xue Chao, Keming Chen, Yuanyuan Xu, Qitao Huang, Jingping Yun, Mei Li, Rongzhen Luo, Jinbo Kuang, Huajia Wang, Haosen Li, Hui Hui, Shuoyu Xu
Format: Article
Language:English
Published: Elsevier 2021-08-01
Series:EBioMedicine
Subjects:
Triple-negative breast cancer
Tumor-infiltrating lymphocyte
Deep learning
Prognosis
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396421002851

Internet

http://www.sciencedirect.com/science/article/pii/S2352396421002851

Similar Items