Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes

Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes

Abstract In addition to traditional biomarkers like PD-(L)1 expression and tumor mutation burden (TMB), more reliable methods for predicting immune checkpoint blockade (ICB) response in cancer patients are urgently needed. This study utilized multiple machine learning approaches on nonsynonymous mut...

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Bibliographic Details
Main Authors: Run Shi, Jing Sun, Zhaokai Zhou, Meiqi Shi, Xin Wang, Zhaojia Gao, Tianyu Zhao, Minglun Li, Yongqian Shu
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:npj Precision Oncology
Online Access:https://doi.org/10.1038/s41698-025-00842-8

Internet

https://doi.org/10.1038/s41698-025-00842-8

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