Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Application value of CT radiomic nomogram in predicting T790M mutation of lung adenocarcinoma.

BMC pulmonary medicine - 11 Sept 2023

Li Xiumei, Chen Jianwei, Zhang Chengxiu, Han Zewen, Zheng Xiuying, Cao Dairong

Abstract excerpt

BACKGROUND: The purpose of this study was to develop a radiomic nomogram to predict T790M mutation of lung adenocarcinoma base on non-enhanced CT lung images. METHODS: This retrospective study reviewed demographic data and lung CT images of 215 lung adenocarcinoma patients with T790M gene test results. 215 patients (including 52 positive) were divided into a training set (n = 150, 36 positive) and an independent...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Adenocarcinoma of Lung
Share to ErbB Receptors

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Lung Neoplasms

Share to Mutation

Share to Nomograms

Share to Protein Kinase Inhibitors

Source

Open in PubMed Open full text

Identifiers

PMID: 37697337
DOI: 10.1186/s12890-023-02609-y
PMCID: PMC10494384

Provenance

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

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Application value of CT radiomic nomogram in predicting T790M mutation of lung adenocarcinoma.PMID 37697337Read ↗

A novel radiomic nomogram for predicting epidermal growth factor receptor mutation in peripheral lung adenocarcinoma.Semantic proximity Read ↗

The Predictive Value of 18F-FDG PET/CT Radiomics in EGFR Gene Mutation of Lung Adenocarcinoma.Semantic proximity Read ↗

The Potential of Radiomics Nomogram in Non-invasively Prediction of Epidermal Growth Factor Receptor Mutation Status and Subtypes in Lung AdenocarcinomaSemantic proximity Read ↗

Radiomics Analysis to Enhance Precise Identification of Epidermal Growth Factor Receptor Mutation Based on Positron Emission Tomography Images of Lung Cancer Patients.Semantic proximity Read ↗

Using CT image-based radiomics to predict EGFR mutations in lung adenocarcinomaSemantic proximity Read ↗

Prediction of EGFR mutation status in non-small cell lung cancer based on multiparametric MRI radiomics.Semantic proximity Read ↗

Accurate prediction of epidermal growth factor receptor mutation status in early-stage lung adenocarcinoma, using radiomics and clinical features.Semantic proximity Read ↗

A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma.Semantic proximity Read ↗

CT delta-radiomics for identification of advanced EGFR-Mutated lung adenocarcinoma Sensitive to Therapies Targeting EGFR PathwaySemantic proximity Read ↗

Using contrast-enhanced CT and non-contrast-enhanced CT to predict EGFR mutation status in NSCLC patients-a radiomics nomogram analysis.Semantic proximity Read ↗

Prediction model based on 18F-FDG PET/CT radiomic features and clinical factors of EGFR mutations in lung adenocarcinoma.Semantic proximity Read ↗

Prediction of EGFR Mutation Status in Non-small Cell Lung Cancer Based on Multiparametric MRI RadiomicsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.