Hepatitis

Effectiveness of Tenofovir Alafenamide in Chronic Hepatitis B Patients with Normal Alanine Aminotransferase and Positive Hepatitis B Virus DNA.

BACKGROUND AND AIMS: With an increasing understanding of hepatitis B, the antiviral indications have been broadening gradually. To evaluate the effectiveness of tenofovir alafenamide (TAF) in chronic hepatitis B (CHB) patients with normal alanine aminotransferase (ALT) and detectable hepatitis B virus (HBV) DNA, those who are ineligible for broader antiviral criteria from the Chinese CHB preventio...

Prediction of African Swine Fever Virus Inhibitors by Molecular Docking-Driven Machine Learning Models.

African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic consequences for global food security. Recent studies have found a few antiviral agents that can inhibit ASFV infections. However, currently, there are no vac...

Alignment-Free Antimicrobial Peptide Predictors: Improving Performance by a Thorough Analysis of the Largest Available Data Set.

In the last two decades, a large number of machine-learning-based predictors for the activities of antimicrobial peptides (AMPs) have been proposed. T...

Detecting Medical Misinformation on Social Media Using Multimodal Deep Learning.

In 2019, outbreaks of vaccine-preventable diseases reached the highest number in the US since 1992. Medical misinformation, such as antivaccine conten...

Predicting direct and indirect non-target impacts of biocontrol agents using machine-learning approaches.

Biological pest control (i.e. 'biocontrol') agents can have direct and indirect non-target impacts, and predicting these effects (especially indirect ...

The adjunct of transcranial direct current stimulation to Robot-assisted therapy in upper limb post-stroke treatment.

Transcranial direct current stimulation (TDCS) and robot-assisted therapy (RAT) proved to be promising interventions in post-stroke rehabilitation. Ho...

Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2.

A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory s...

Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis.

BACKGROUND: COVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment...

Force-Free Control for Direct Teaching of a Surgical Assistant Robot End Effector with Wire-Driven Bidirectional Telescopic Mechanism.

This paper shows the design and modeling of an end effector with a bidirectional telescopic mechanism to allow a surgical assistant robot to hold and ...

Prediction of direct carbon emissions of Chinese provinces using artificial neural networks.

Closely connected to human carbon emissions, global climate change is affecting regional economic and social development, natural ecological environme...

Selecting a stable solid form of remdesivir using microcrystal electron diffraction and crystal structure prediction.

Therapeutic options in response to the coronavirus disease 2019 (COVID-19) outbreak are urgently needed. In this communication, we demonstrate how to ...

Detection of liver cirrhosis in standard T2-weighted MRI using deep transfer learning.

OBJECTIVES: To investigate the diagnostic performance of deep transfer learning (DTL) to detect liver cirrhosis from clinical MRI.

Article-level classification of scientific publications: A comparison of deep learning, direct citation and bibliographic coupling.

Classification schemes for scientific activity and publications underpin a large swath of research evaluation practices at the organizational, governm...

Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade.

: Drug design and discovery of new antivirals will always be extremely important in medicinal chemistry, taking into account known and new viral disea...

An artificial intelligence algorithm for analyzing acetaminophen-associated toxic hepatitis.

INTRODUCTION: Very little artificial intelligence (AI) work has been performed to investigate acetaminophen-associated hepatotoxicity. The objective o...

Feasibility of automatic detection of small hepatocellular carcinoma (≤2 cm) in cirrhotic liver based on pattern matching and deep learning.

Early detection of hepatocellular carcinoma (HCC) is crucial for clinical management. Current studies have reported large HCC detections using automat...

Application of deep learning and molecular modeling to identify small drug-like compounds as potential HIV-1 entry inhibitors.

A generative adversarial autoencoder for the rational design of potential HIV-1 entry inhibitors able to block CD4-binding site of the viral envelope ...

GraphCovidNet: A graph neural network based model for detecting COVID-19 from CT scans and X-rays of chest.

COVID-19, a viral infection originated from Wuhan, China has spread across the world and it has currently affected over 115 million people. Although v...

Simpson's Paradox in COVID-19 Case Fatality Rates: A Mediation Analysis of Age-Related Causal Effects.

We point out an instantiation of Simpson's paradox in COVID-19 case fatality rates (cfrs): comparing a large-scale study from China (February 17) with...

An Explainable Artificial Intelligence Framework for the Deterioration Risk Prediction of Hepatitis Patients.

In recent years, artificial intelligence-based computer aided diagnosis (CAD) system for the hepatitis has made great progress. Especially, the comple...