Deep learning for survival prediction in triple-negative breast cancer: development and validation in real-world cohorts

Deep learning for survival prediction in triple-negative breast cancer: development and validation in real-world cohorts

Abstract Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous disease, highlighting the need for better patient stratification to guide treatment. We developed a deep learning-based survival model and an individualized prognosis system using data from 37,818 TNBC patients in the S...

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Bibliographic Details
Main Authors: Yiyue Xu, Butuo Li, Bing Zou, Bingjie Fan, Shijiang Wang, Jinming Yu, Taotao Dong, Linlin Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Triple-negative breast cancer
Deep learning
Prognosis model
Survival prediction system
Online Access:https://doi.org/10.1038/s41598-025-16331-8
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https://doi.org/10.1038/s41598-025-16331-8

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