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An Integrated Clinical‐Radiomics‐Deep Learning Model Based on 18F‐FDG PET/CT for Predicting EGFR Mutation Status in Lung Adenocarcinoma

ABSTRACT Background An integrated model combining clinical variables, radiomic features, and deep learning was developed to predict EGFR mutation status in patients with lung adenocarcinoma based on pretreatment 18F‐FDG PET/CT imaging. Methods In this retrospective study, data from 218 patients—incl...

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Principais autores: Yun Wang, Zhaoqing Chen, Jing Li, Yuhuang Cai, Chengyang Sun, Jingjing Zhang, Marcus Hacker, Xiang Li, Heqing Yi
Format: Artigo
Sprog:Inglês
Udgivet: Wiley 2025-11-01
Serier:Cancer Medicine
Fag:
18F‐FDG PET/CT
deep learning
epidermal growth factor receptor
lung adenocarcinoma
Online adgang:https://doi.org/10.1002/cam4.71370
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