Machine learning approaches for EGFR mutation status prediction in NSCLC: an updated systematic review

Machine learning approaches for EGFR mutation status prediction in NSCLC: an updated systematic review

BackgroundWith the rapid advances in artificial intelligence—particularly convolutional neural networks—researchers now exploit CT, PET/CT and other imaging modalities to predict epidermal growth factor receptor (EGFR) mutation status in non-small-cell lung cancer (NSCLC) non-invasively, rapidly and...

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Bibliographic Details
Main Authors: Liu Haixian, Pang Shu, Li Zhao, Lu Chunfeng, Li Lun
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Oncology
Subjects:
artificial intelligence
Non-small cell lung cancer (NSCLC)
EGFR mutation
deep learning
medical imaging
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1576461/full
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