Infectious Disease

Hepatitis

Latest AI and machine learning research in hepatitis for healthcare professionals.

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Hepatitis C Virus Saint Petersburg Variant Detection With Machine Learning Methods.

Hepatitis C virus infection is a significant global health concern, affecting millions worldwide. Al...

Development and Validation of a Novel Model to Discriminate Idiosyncratic Drug-Induced Liver Injury and Autoimmune Hepatitis.

BACKGROUND AND AIM: Discriminating between idiosyncratic drug-induced liver injury (DILI) and autoim...

VirusImmu: a novel ensemble machine learning approach for viral immunogenicity prediction.

The viruses threats provoke concerns regarding their sustained epidemic transmission, making the dev...

Enterotype-stratified gut microbial signatures in MASLD and cirrhosis based on integrated microbiome data.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global h...

Identification of hub gene for the pathogenic mechanism and diagnosis of MASLD by enhanced bioinformatics analysis and machine learning.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a heterogeneous disease caused b...

Artificial intelligence in vaccine research and development: an umbrella review.

BACKGROUND: The rapid development of COVID-19 vaccines highlighted the transformative potential of a...

Waist rotation angle as indicator of probable human collision-avoidance direction for autonomous mobile robots.

The likelihood of pedestrians encountering autonomous mobile robots (AMRs) in smart cities is steadi...

Vaccination hesitancy: agreement between WHO and ChatGPT-4.0 or Gemini Advanced.

BACKGROUND: An increasing number of individuals use online Artificial Intelligence (AI) - based chat...

EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides.

BACKGROUND: The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwi...

An Integrated Approach to Develop a Potent Vaccine Candidate Construct Against Prostate Cancer by Utilizing Machine Learning and Bioinformatics.

BACKGROUND: Prostate cancer is the most common malignancy among males. Prostaglandin G/H synthase (P...

Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics.

Recent advances in single-cell RNA-Sequencing (scRNA-Seq) technologies have revolutionized our abili...

microT-CNN: an avant-garde deep convolutional neural network unravels functional miRNA targets beyond canonical sites.

microRNAs (miRNAs) are central post-transcriptional gene expression regulators in healthy and diseas...

Review on article of preoperative prediction in chronic hepatitis B virus patients using spectral computed tomography and machine learning.

This letter comments on the article that developed and tested a machine learning model that predicts...

Evaluation of alarm notification of artificial intelligence in automated analyzer detection of parasites.

To evaluate the alarm notification of artificial intelligence in detecting parasites on the KU-F40 F...

Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders.

The COVID-19 pandemic is marked by the successive emergence of new SARS-CoV-2 variants, lineages, an...

MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework.

The gut microbiota plays a vital role in human health, and significant effort has been made to predi...

Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis.

We sought to develop and validate a machine learning (ML) model for predicting multidimensional frai...

Antiviral Effectiveness, Clinical Outcomes, and Artificial Intelligence Imaging Analysis for Hospitalized COVID-19 Patients Receiving Antivirals.

INTRODUCTION: There is still a lack of clinical evidence comprehensively evaluating the effectivenes...

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