Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma

Abstract Background Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study aims to develop a deep learning radiologi...

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Bibliographic Details
Main Authors: Taotao Yang, Xianqi Wang, Yuan Jin, Xiaohong Yao, Zhiyuan Sun, Pinzhen Chen, Suyi Zhou, Wentao Zhu, Wei Chen
Format: Article
Language:English
Published: BMC 2025-04-01
Series:Journal of Translational Medicine
Subjects:
CT
WSI
Deep learning
EGFR
Targeted therapy
Multi-modality
Online Access:https://doi.org/10.1186/s12967-025-06480-9
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https://doi.org/10.1186/s12967-025-06480-9

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