ObjectiveThe purpose of this study was to evaluate the diagnostic performance of computed tomography (CT) scan–based radiomics in prediction of lymph node metastasis (LNM) in gastric cancer (GC) patients.MethodsPubMed, Embase, Web of Science, and Cochrane Library databases were searched for original studies published until 10 November 2022, and the studies satisfying the inclusion criteria were included. Characteristics of included studies and radiomics approach and data for constructing 2 × 2 tables were extracted. The radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) were utilized for the quality assessment of included studies. Overall sensitivity, specificity, diagnostic odds ratio (DOR), and ...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival and...
PURPOSE: To build and validate a radiomics-based nomogram for the prediction of pre-operation lymph ...
ObjectiveThe purpose of this study was to evaluate the diagnostic performance of computed tomography...
Background: To evaluate whether radiomic feature-based computed tomography (CT) imaging signatures a...
ObjectiveTo investigate the role of pre-treatment magnetic resonance imaging (MRI) radiomics for the...
BackgroundTo assess the predictive value of radiomics for preoperative lymph node metastasis (LMN) i...
Background: To evaluate whether radiomic feature-based computed tomography (CT) imaging signatures a...
Background: The aim of this study was to identify the increased value of integrating computed tomogr...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
Background: Accurate evaluation of human epidermal growth factor receptor 2 (HER2) status is of grea...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival and...
PURPOSE: To build and validate a radiomics-based nomogram for the prediction of pre-operation lymph ...
ObjectiveThe purpose of this study was to evaluate the diagnostic performance of computed tomography...
Background: To evaluate whether radiomic feature-based computed tomography (CT) imaging signatures a...
ObjectiveTo investigate the role of pre-treatment magnetic resonance imaging (MRI) radiomics for the...
BackgroundTo assess the predictive value of radiomics for preoperative lymph node metastasis (LMN) i...
Background: To evaluate whether radiomic feature-based computed tomography (CT) imaging signatures a...
Background: The aim of this study was to identify the increased value of integrating computed tomogr...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
Background: Accurate evaluation of human epidermal growth factor receptor 2 (HER2) status is of grea...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
BackgroundThis study aims to develop and validate a predictive model combining deep transfer learnin...
To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival and...
PURPOSE: To build and validate a radiomics-based nomogram for the prediction of pre-operation lymph ...