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Article

Deep learning-radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients.

Scientific reports - 9 Jan 2024

Kim Seonhwa, Lim June Hyuck, Kim Chul-Ho, Roh Jin, You Seulgi, Choi Jeong-Seok, Lim Jun Hyeok, Kim Lucia, Chang Jae Won, Park Dongil, Lee Myung-Won, Kim Sup, Heo Jaesung

Abstract excerpt

This study focused on a novel strategy that combines deep learning and radiomics to predict epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC) using computed tomography (CT). A total of 1280 patients with NSCLC who underwent contrast-enhanced CT scans and EGFR mutation testing before treatment were selected for the final study. Regions of interest were segmented...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 38195717
DOI: 10.1038/s41598-024-51630-6
PMCID: PMC10776765

Provenance

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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