The hepatitis B virus (HBV) remains a global problem despite effective tools to prevent,
diagnosis, and control it. Unmet needs are identifiable across its clinical care cascade …

Unlocking the future: Machine learning sheds light on prognostication for early-stage
hepatocellular carcinoma: Editorial on “Conventional and machine learning- based risk scores …

Abstract Background & Aims: Liver stiffness measurement (LSM) via vibration-controlled
transient elastography (VCTE) accurately assesses fibrosis. We aimed to develop a …

The integration of artificial intelligence (AI) into hepatology is revolutionizing the diagnosis
and management of liver diseases amidst a rising global burden of conditions like metabolic …

PURPOSE Postsustained virologic response (SVR) screening following clinical guidelines
does not address individual risk of hepatocellular carcinoma (HCC). Our aim is to provide …

In this issue of NEJM Evidence, Gu et al. introduce a novel risk stratification algorithm to
apply to patients with advanced chronic liver disease (ACLD) who are at risk of develo** …

ABSTRACT Background and Aims This study aims to develop and validate a machine
learning (ML) model predicting hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) …

Background Besides tumorous information, synergistic liver parenchyma assessments may
provide additional insights into the prognosis of hepatocellular carcinoma (HCC). This study …

Background & Aims Various hepatocellular carcinoma (HCC) prediction models have been
proposed for patients with chronic hepatitis B (CHB) using clinical variables. We aimed to …

Background & Aims Direct-acting antivirals (DAAs) have considerably improved chronic
hepatitis C (HCV) treatment; however, follow-up after sustained virological response (SVR) …