PurposeMachine learning (ML) can extract high-throughput features of images to predict disease. This study aimed to develop nomogram of multi-parametric MRI (mpMRI) ML model to predict the risk of bre
I uploaded the extracted features on Magnetic Resonance VIBE hepatobiliary phase of the publication accepted on Radiologia Medica: Machine learning-based radiomics analysis in predicting RAS mutationa
BackgroundThis study aims to investigate the predicting value of Automated Breast Volume Scanner (ABVS) combined with Virtual Touch Imaging and Quantification (VTIQ) for axillary lymph node (ALN) meta
ObjectivesQuantitatively assess the severity and predict the mortality of interstitial lung disease (ILD) associated with Rheumatoid arthritis (RA) was a challenge for clinicians. This study aimed to
BackgroundEndoscopic submucosal dissection (ESD) has been accepted as the standard treatment for the appropriate indication of early gastric cancer (EGC). Determining the risk of lymph node metastasis
