Hepatitis

Use of Deep Learning to Analyze Social Media Discussions About the Human Papillomavirus Vaccine.

IMPORTANCE: Human papillomavirus (HPV) vaccine hesitancy or refusal is common among parents of adolescents. An understanding of public perceptions from the perspective of behavior change theories can facilitate effective and targeted vaccine promotion strategies.

An index based on deep learning-measured spleen volume on CT for the assessment of high-risk varix in B-viral compensated cirrhosis.

OBJECTIVES: Deep learning enables an automated liver and spleen volume measurements on CT. The purpose of this study was to develop an index combining liver and spleen volumes and clinical factors for detecting high-risk varices in B-viral compensated cirrhosis.

An Interpretable Predictive Model of Vaccine Utilization for Tanzania.

Providing accurate utilization forecasts is key to maintaining optimal vaccine stocks in any health facility. Current approaches to vaccine utilizatio...

Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.

The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity a...

Virgin Coconut Oil-Induced Neuroprotection in Lipopolysaccharide-Challenged Rats is Mediated, in Part, Through Cholinergic, Anti-Oxidative and Anti-Inflammatory Pathways.

Neuroinflammation is associated with neuronal cell death and could lead to chronic neurodegeneration. This study investigated the neuroprotective pote...

Deep learning based detection and analysis of COVID-19 on chest X-ray images.

Covid-19 is a rapidly spreading viral disease that infects not only humans, but animals are also infected because of this disease. The daily life of h...

A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks.

The use of imaging data has been reported to be useful for rapid diagnosis of COVID-19. Although computed tomography (CT) scans show a variety of sign...

Artificial Intelligence Applied to Gene Expression Testing (IVIGET) to Predict Trivalent Inactivated Influenza Vaccine Immunogenicity in HIV Infected Children.

The number of patients affected by chronic diseases with special vaccination needs is burgeoning. In this scenario, predictive markers of immunogenici...

A Novel Strategy for the Development of Vaccines for SARS-CoV-2 (COVID-19) and Other Viruses Using AI and Viral Shell Disorder.

A model that predicts levels of coronavirus (CoV) respiratory and fecal-oral transmission potentials based on the shell disorder has been built using ...

Peginterferon and Entecavir Combination Therapy Improves Outcome of Non-Early Response Hepatitis B e Antigen-Positive Patients.

BACKGROUND: The efficacy of nucleot(s)ide analogs (NAs) and pegylated interferon (PegIFN) combination therapy for hepatitis B e antigen-positive (HBeA...

Evolutionary artificial intelligence based peptide discoveries for effective Covid-19 therapeutics.

An epidemic caused by COVID-19 in China turned into pandemic within a short duration affecting countries worldwide. Researchers and companies around t...

Viral pandemic preparedness: A pluripotent stem cell-based machine-learning platform for simulating SARS-CoV-2 infection to enable drug discovery and repurposing.

Infection with the SARS-CoV-2 virus has rapidly become a global pandemic for which we were not prepared. Several clinical trials using previously appr...

Alcoholic liver disease: A registry view on comorbidities and disease prediction.

Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Sustained excess drinking causes fatty liver and alc...

Prediction of hepatitis E using machine learning models.

BACKGROUND: Accurate and reliable predictions of infectious disease can be valuable to public health organizations that plan interventions to decrease...

Development of machine learning-based clinical decision support system for hepatocellular carcinoma.

There is a significant discrepancy between the actual choice for initial treatment option for hepatocellular carcinoma (HCC) and recommendations from ...

Molecular barcoding of native RNAs using nanopore sequencing and deep learning.

Nanopore sequencing enables direct measurement of RNA molecules without conversion to cDNA, thus opening the gates to a new era for RNA biology. Howev...

Hydroxyl Radical Generation Through the Fenton-Like Reaction of Hematin- and Catechol-Functionalized Microgels.

Hydroxyl radical (OH) is a potent reactive oxygen species with the ability to degrade hazardous organic compounds, kill bacteria, and inactivate virus...

Assessment of a Deep Learning Model to Predict Hepatocellular Carcinoma in Patients With Hepatitis C Cirrhosis.

IMPORTANCE: Deep learning, a family of machine learning models that use artificial neural networks, has achieved great success at predicting outcomes ...

GeFeS: A generalized wrapper feature selection approach for optimizing classification performance.

In this paper, we propose a generalized wrapper-based feature selection, called GeFeS, which is based on a parallel new intelligent genetic algorithm ...

Machine learning for clinical trials in the era of COVID-19.

The world is in the midst of a pandemic. We still know little about the disease COVID-19 or about the virus (SARS-CoV-2) that causes it. We do not hav...