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Artificial Intelligence-Based Model Exploiting Hematoxylin and Eosin Images to Predict Rare Gene Mutations in Patients With Lung Adenocarcinoma.

JCO clinical cancer informatics - 1 Sept 2025

Yu Peiling, Chen Weixing, Liu Nan, Yu Yang, Guo Hongyu, Yuan Yinan, Guo Weilin, Alatan Yini, Zhao Jinming, Su Hongbo, Nie Siru, Cui Xiaoyu, Miao Yuan

Abstract excerpt

PURPOSE: Accurately identifying gene mutations in lung cancer is crucial for treatment, while molecular diagnostic methods are time-consuming and complex. This study aims to develop an advanced deep learning model to address this issue. METHODS: In this study, the ResNeXt101 model framework was established to predict the gene mutation status in lung adenocarcinoma. The model was trained and validated using data...

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Adenocarcinoma of Lung
Artificial Intelligence
Biomarkers, Tumor
Deep Learning
Lung Neoplasms

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 41004706
DOI: 10.1200/CCI-25-00093
PMCID: PMC12487657

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 1 Sept 2026.

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