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Article

Using Vision Transformer for high robustness and generalization in predicting EGFR mutation status in lung adenocarcinoma.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico - 1 Jun 2024

Weng Luoqi, Xu Yilun, Chen Yuhan, Chen Chengshui, Qian Qinqing, Pan Jie, Su Huang

Abstract excerpt

BACKGROUND: Lung adenocarcinoma is a common cause of cancer-related deaths worldwide, and accurate EGFR genotyping is crucial for optimal treatment outcomes. Conventional methods for identifying the EGFR genotype have several limitations. Therefore, we proposed a deep learning model using non-invasive CT images to predict EGFR mutation status with robustness and generalizability. METHODS: A total of 525 patients...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 38194018
DOI: 10.1007/s12094-023-03366-4

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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