View clinical trials related to Radiomics.
Filter by:In addition to kidney tumor specific factors, adherent perirenal fat is one of the most important causes of technical complications in kidney surgery, and currently, there is a lack of widely used non-invasive predictive models in clinical practice. In this study, a deep learning algorithm based on CT imaging and nomogram was proposed to identify and predict the presence of adherent perirenal fat. This study includes the construction of a prediction model based on CT imaging and the verification of the prediction model.
The goal of this observational study is to explore the role of prediction of microvascular invasion by radiomics based on pre-treatment magnetic resonance imaging for guiding treatment of Barcelona Clinic Liver Cancer stage B hepatocellular carcinoma.