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Tackling Tumor Heterogeneity Issue: Transformer-Based Multiple Instance Enhancement Learning for Predicting EGFR Mutation via CT Images.

IEEE transactions on medical imaging - 1 Nov 2025

Fang Yulin, Wang Minghui, Song Qilong, Cao Chi, Gao Ziyu, Song Biao, Min Xuhong, Li Ao

Abstract excerpt

Accurate and non-invasive prediction of epidermal growth factor receptor (EGFR) mutation is crucial for the diagnosis and treatment of non-small cell lung cancer (NSCLC). While computed tomography (CT) imaging shows promise in identifying EGFR mutation, current prediction methods heavily rely on fully supervised learning, which overlooks the substantial heterogeneity of tumors and therefore leads to suboptimal...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 40504719
DOI: 10.1109/TMI.2025.3578995

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EGFR

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