Deep learning is a branch of artificial intelligence where networks of simple interconnected
units are used to extract patterns from data in order to solve complex problems. Deep …

Background & Aims The Liver Imaging Reporting and Data System (LI-RADS) categorizes
observations from imaging analyses of high-risk patients based on the level of suspicion for …

Objectives To develop and validate a radiomics nomogram for preoperative prediction of
microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Methods The …

Importance Long-term oncologic outcomes of robotic surgery remain a hotly debated topic in
surgical oncology, but sparse data have been published thus far. Objective To analyze short …

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major
public health problem worldwide. Hepatocarcinogenesis is a complex multistep process at …

The Liver Imaging Reporting and Data System (LI-RADS®) is a comprehensive system for
standardizing the terminology, technique, interpretation, reporting, and data collection of …

To detect potentially curable hepatocellular carcinoma (HCC), clinical practice guidelines
recommend semiannual surveillance US of the liver in adult patients at risk for developing …

Radiomics is an emerging field which extracts quantitative radiology data from medical
images and explores their correlation with clinical outcomes in a non-invasive manner. This …

Observer-driven pattern recognition is the standard for interpretation of medical images. To
achieve global parity in interpretation, semi-quantitative scoring systems have been …

Objectives To investigate the performance of the Liver Imaging Reporting and Data System
(LI-RADS) v2017 for combined hepatocellular cholangiocarcinoma (cHCC-CCA) in the …