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Article

Machine learning-based radiomics strategy for prediction of acquired EGFR T790M mutation following treatment with EGFR-TKI in NSCLC.

Scientific reports - 3 Jan 2024

Lu Jiameng, Ji Xiaoqing, Liu Xinyi, Jiang Yunxiu, Li Gang, Fang Ping, Li Wei, Zuo Anli, Guo Zihan, Yang Shuran, Ji Yanbo, Lu Degan

Abstract excerpt

The epidermal growth factor receptor (EGFR) Thr790 Met (T790M) mutation is responsible for approximately half of the acquired resistance to EGFR-tyrosine kinase inhibitor (TKI) in non-small-cell lung cancer (NSCLC) patients. Identifying patients at diagnosis who are likely to develop this mutation after first- or second-generation EGFR-TKI treatment is crucial for better treatment outcomes. This study aims to...

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Identifiers

PMID: 38172228
DOI: 10.1038/s41598-023-50984-7
PMCID: PMC10764785

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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