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Hepatitis B, Chronic

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A baseline model including quantitative anti-HBc to predict response of peginterferon in HBeAg-positive chronic hepatitis B patients.

Antiviral therapy
BACKGROUND: Few models to predict antiviral response of peginterferon were used in hepatitis B e antigen (HBeAg)-positive chronic hepatitis B patients and the prediction efficacy was unsatisfied. Quantitative antibody to hepatitis B core antigen (ant...

The role of quantitative HBsAg in the natural history of e antigen-negative chronic hepatitis B: A Tunisian prospective study.

Infectious diseases now
BACKGROUND/AIMS: During the natural course of Chronic Hepatitis B (CHB) infection, differentiation between inactive carrier (IC) and HBeAg negative CHB is a subject of ongoing debate. We studied the role of hepatitis B surface antigen (HBsAg) level a...

Deep Learning in the Classification of Stage of Liver Fibrosis in Chronic Hepatitis B with Magnetic Resonance ADC Images.

Contrast media & molecular imaging
Liver fibrosis in chronic hepatitis B is the pathological repair response of the liver to chronic injury, which is a key step in the development of various chronic liver diseases to cirrhosis and an important link affecting the prognosis of chronic l...

High-dimensional hepatopath data analysis by machine learning for predicting HBV-related fibrosis.

Scientific reports
Chronic HBV infection, the main cause of liver cirrhosis and hepatocellular carcinoma, has become a global health concern. Machine learning algorithms are particularly adept at analyzing medical phenomenon by capturing complex and nonlinear relations...

An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B.

Journal of hepatology
BACKGROUND & AIMS: Several models have recently been developed to predict risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). Our aims were to develop and validate an artificial intelligence-assisted prediction model of...

Optimizing hepatitis B virus screening in the United States using a simple demographics-based model.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression (LR) and machine learning (ML; random forest) mod...

Diagnosis of significant liver fibrosis in patients with chronic hepatitis B using a deep learning-based data integration network.

Hepatology international
BACKGROUND AND AIMS: Chronic hepatitis B virus (CHB) infection remains a major global health burden and the non-invasive and accurate diagnosis of significant liver fibrosis (≥ F2) in CHB patients is clinically very important. This study aimed to ass...

A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with chronic hepatitis B.

European radiology
OBJECTIVE: To develop and investigate a deep learning model with data integration of ultrasound contrast-enhanced micro-flow (CEMF) cines, B-mode images, and patients' clinical parameters to improve the diagnosis of significant liver fibrosis (≥ F2) ...

Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection.

Clinical and molecular hepatology
BACKGROUND/AIMS: The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is paramount for effective management. This study aimed to evaluate the prognostic value of computed tomography (CT) analysis using deep learning algorith...