Latest AI and machine learning research in hepatitis for healthcare professionals.
BACKGROUND: This study aimed to develop prognostic models for predicting 28- and 90-day mortality ra...
Antiviral peptides (AVPs) have been experimentally verified to block virus into host cells, which ha...
BACKGROUND: We developed a system to automatically classify stance towards vaccination in Twitter me...
Recently, the inflammation of the intestinal mucosa has been related to many diseases in humans and ...
Several European countries have established criteria for prioritising initiation of treatment in pat...
Biomarker estimation methods from medical images have traditionally followed a segment-and-measure s...
Identification of neoantigens is a critical step in predicting response to checkpoint blockade thera...
Chronic infection with Hepatitis B virus (HBV) is a major risk factor for the development of advance...
BACKGROUND: Body composition is increasingly being recognized as an important prognostic factor for ...
PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vacc...
In the twenty-first century, high contagious infectious diseases such as SARS (Severe Acute Respirat...
BACKGROUND: Antiretroviral therapy (ART) has significantly reduced HIV-related morbidity and mortali...
BACKGROUND: Liver transplantation (LT) is an accepted therapeutic option for hepatocellular carcinom...
Without decomposing complex-valued systems into real-valued systems, this paper investigates existen...
Liver disease causes millions of deaths per year worldwide, and approximately half of these cases ar...
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 25-30% of the general population and i...
Global outbreaks caused by emerging or re-emerging arthropod-borne viruses (arboviruses) are becomi...
BACKGROUND AND AIM: Loss of hepatitis B surface antigen (HBsAg) is an important goal in the treatmen...
Machine learning has the potential to identify novel biological factors underlying successful antibo...
Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging re...
A framework for clinical diagnosis which uses bioinspired algorithms for feature selection and gradi...