Radiomics is a method to extract detailed information from diagnostic images that cannot be
perceived by the naked eye. Although radiomics research carries great potential to improve …

Radiomics allows the extraction of quantitative imaging features from clinical magnetic
resonance imaging (MRI) and computerized tomography (CT) studies. The advantages of …

Background New machine learning methods and techniques are frequently introduced in
radiomics, but they are often tested on a single dataset, which makes it challenging to …

Background The metastatic vascular patterns of hepatocellular carcinoma (HCC) are mainly
microvascular invasion (MVI) and vessels encapsulating tumor clusters (VETC). However …

Backgrounds Anti‐vascular endothelial growth factor (VEGF) therapy has been developed
and recognized as an effective treatment for hepatocellular carcinoma (HCC). However …

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, with an
increasing incidence and poor prognosis. In the past decade, artificial intelligence (AI) …

Liver transplantation (LT) is the recommended curative-intent treatment for patients with
early or intermediate-stage hepatocellular carcinoma (HCC) who are ineligible for resection …

The incidence and mortality of pancreatic ductal adenocarcinoma (PDAC) are rising. It is
projected that PDAC will become the second leading cause of cancer death in the USA …

Background This study aims to develop habitat radiomic models to predict overall survival
(OS) for hepatocellular carcinoma (HCC), based on the characterization of the intratumoral …

Hepatic diffuse conditions and focal liver lesions represent two of the most common
scenarios to face in everyday radiological clinical practice. Thanks to the advances in …