ArticleAnnals of translational medicine2021
A computed tomography (CT)-derived radiomics approach for predicting primary co-mutations involving
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prediction of oncogene mutation status in non-small cell lung cancer: a systematic review and meta-analysis with a special focus on artificial intelligence-based methods.European radiology · 2026Pooled it
- Machine learning approaches for EGFR mutation status prediction in NSCLC: an updated systematic review.Frontiers in oncology · 2025Pooled it
- Treatment patterns and clinical outcomes in Chinese patients with NSCLC withMolecular and clinical oncology · 2025Article
- Prediction of EGFR-TP53 genes co-mutations in patients with lung adenocarcinoma (LUAD) byClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Development and validation of a DNA damage repair-related gene-based prediction model for the prognosis of lung adenocarcinoma.Journal of thoracic disease · 2023Article
- An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma.Heliyon · 2023Article
- Application value of a computer-aided diagnosis and management system for the detection of lung nodules.Quantitative imaging in medicine and surgery · 2023Article
- CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing.Frontiers in medicine · 2023Article
- Identification and validation of a hypoxia-immune signature for overall survival prediction in lung adenocarcinoma.Frontiers in genetics · 2022Article
- Deep Radiotranscriptomics of Non-Small Cell Lung Carcinoma for Assessing Molecular and Histology Subtypes with a Data-Driven Analysis.Diagnostics (Basel, Switzerland) · 2021Article
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Abstract
backgroundEpidermal growth factor receptor ( EGFR: mutated lung adenocarcinomas (LUAD). To identify this genetically unique subset prior to treatment through computed tomography (CT) images had not been reported yet.
methodsStage III and IV LUAD with known mutation status of
resultsA total of 199 patients were enrolled, including 83 (42%) cases of
conclusionsCT imaging based artificial intelligence (AI) is expected to distinguish co-mutation status involving
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