The implementation of low-dose chest CT for lung screening presents a crucial opportunity
to advance lung cancer care through early detection and interception. In addition, millions of …

Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of
cancer-associated deaths. In recent years, significant progress has been achieved in basic …

Background This study aims to construct radiomics models based on [18F] FDG PET/CT
using multiple machine learning methods to predict the EGFR mutation status of lung …

Purpose To develop and interpret optimal predictive models to identify epidermal growth
factor receptor (EGFR) mutation status and subtypes in patients with lung adenocarcinoma …

Objective This study aimed to evaluate the value of 18 F-FDG PET/CT radiomics in
predicting EGFR gene mutations in non-small cell lung cancer by meta-analysis. Methods …

(1) Background: To investigate the association between maximum standardized uptake
value (SUVmax) based on 18F-FDG PET/CT and EGFR mutation status in lung …

Purpose To develop and evaluate the performance of radiomics-based computed
tomography (CT) combined with machine learning algorithms in detecting occult vertebral …

The earlier identification of EGFR mutation status in lung adenocarcinoma patients is crucial
for treatment decision-making. Radiomics, which involves high-throughput extraction of …

Objectives To establish and validate a radiomics nomogram model for preoperative
prediction of KIT exon 9 mutation status in patients with gastrointestinal stromal tumors …

Background In non small cell lung cancer (NSCLC), alternative strategies to determine
patient oncogene mutation status are essential to overcome some of the drawbacks …