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Article

Deep learning framework for predicting EGFR mutation status from H&E whole slide images in lung adenocarcinoma.

BMC cancer - 1 Apr 2026

Shao Weiwei, Gu Wenyue, Song Shu, Chen Danyi, Shao Zhongming, Sun Qian, Yu Hong

Abstract excerpt

BACKGROUND: Epidermal growth factor receptor (EGFR) mutations are pivotal molecular drivers in lung adenocarcinoma (LUAD) with significant therapeutic implications, yet conventional molecular testing remains costly, time-consuming, and limited by tissue availability. This study aimed to develop and validate a pathology-based predictive model that integrates deep learning and machine learning to identify EGFR...

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Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 41923035
DOI: 10.1186/s12885-026-15957-9
PMCID: PMC13169861

Genes

EGFR

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