Multimodal Deep Learning Integrating Tumor Radiomics and Mediastinal Adiposity Improves Survival Prediction in Non‐Small Cell Lung Cancer: A Prognostic Modeling Study

Multimodal Deep Learning Integrating Tumor Radiomics and Mediastinal Adiposity Improves Survival Prediction in Non‐Small Cell Lung Cancer: A Prognostic Modeling Study

ABSTRACT Background and Purpose Prognostic stratification in non‐small cell lung cancer (NSCLC) presents considerable challenges due to tumor heterogeneity. Emerging evidence has proposed that adipose tissue may play a prognostic role in oncological outcomes. This study investigates the integration...

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Bibliographic Details
Main Authors: Ye Niu, Han‐bing Xie, Hao‐bo Jia, Lin Zhao, Le Liu, Ping‐ping Liu, Xue‐meng Li, Rui‐tao Wang, Yuan‐zhou Li
Format: Article
Language:English
Published: Wiley 2025-08-01
Series:Cancer Medicine
Subjects:
computerized tomography
deep learning
mediastinal fat
non‐small cell lung cancer
survival
Online Access:https://doi.org/10.1002/cam4.71077
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