Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer

Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer

Abstract Breast cancer is the most common type of cancer in women, and while current treatments can cure the majority of early-stage primary BC cases, recurrence remains a significant challenge. Traditional methods of assessing patient prognosis, such as AJCC, TNM staging, and biochemical markers, a...

Full description

Saved in:
Bibliographic Details
Main Authors: Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:Scientific Reports
Subjects:
Data mining
Prognosis
Immune microenvironment
Expression difference
Functional enrichment analysis
Machine learning
Online Access:https://doi.org/10.1038/s41598-025-03423-8
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items