Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response

Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response

IntroductionHead and neck squamous cell carcinoma (HNSCC), a highly heterogeneous malignancy is often associated with unfavorable prognosis. Due to its unique anatomical position and the absence of effective early inspection methods, surgical intervention alone is frequently inadequate for achieving...

Full description

Saved in:
Bibliographic Details
Main Authors: Sha-Zhou Li, Hai-Ying Sun, Yuan Tian, Liu-Qing Zhou, Tao Zhou
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Immunology
Subjects:
machine learning
HNSCC
DEGs
tumor microenvironment
immunotherapy
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2024.1469895/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.frontiersin.org/articles/10.3389/fimmu.2024.1469895/full

Similar Items