Integrative machine learning model for subtype identification and prognostic prediction in lung squamous cell carcinoma

Integrative machine learning model for subtype identification and prognostic prediction in lung squamous cell carcinoma

Abstract Background Lung squamous cell carcinoma (LUSC) is a leading cause of cancer-related mortality, and tumor heterogeneity could result in diverse prognostic subtypes. Traditional prognostic factors, like tumor, node, and metastasis (TNM) staging, offer limited predictive accuracy. This study a...

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Bibliographic Details
Main Authors: Guangliang Duan, Qi Huo, Wei Ni, Fei Ding, Yuefang Ye, Tingting Tang, Huiping Dai
Format: Article
Language:English
Published: Springer 2025-05-01
Series:Discover Oncology
Subjects:
Lung squamous cell carcinoma
Unsupervised clustering
Survival prediction
Chemotherapy
Machine learning
Online Access:https://doi.org/10.1007/s12672-025-02560-w
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https://doi.org/10.1007/s12672-025-02560-w

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