Hepatitis

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms.

RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testing has provided some key insights on how RNA vaccines interact with the innate immune system, their mechanism of action appears to be fragmented amid t...

Predicting mortality among patients with liver cirrhosis in electronic health records with machine learning.

OBJECTIVE: Liver cirrhosis is a leading cause of death and effects millions of people in the United States. Early mortality prediction among patients with cirrhosis might give healthcare providers more opportunity to effectively treat the condition. We hypothesized that laboratory test results and other related diagnoses would be associated with mortality in this population. Our another assumption...

Deep learning-based image reconstruction for TOF PET with DIRECT data partitioning format.

Conventional positron emission tomography (PET) image reconstruction is achieved by the statistical iterative method. Deep learning provides another o...

Machine Learning Approach for Active Vaccine Safety Monitoring.

BACKGROUND: Vaccine safety surveillance is important because it is related to vaccine hesitancy, which affects vaccination rate. To increase confidenc...

A model based on clinico-biochemical characteristics and deep learning features from MR images for assessing necroinflammatory activity in chronic hepatitis B.

Hybrid Machine Learning Models for Predicting Types of Human T-cell Lymphotropic Virus.

Life threatening diseases like adult T-cell leukemia, neurodegenerative diseases, and demyelinating diseases such as HTLV-1 based myelopathy/tropical ...

Improving streamflow simulation by combining hydrological process-driven and artificial intelligence-based models.

Accurate and timely monitoring of streamflow and its variation is crucial for water resources management in watersheds. This study aimed at evaluating...

Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets.

COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures...

Efficacy and safety of an open lung ventilation strategy with staircase recruitment followed by comparison on two different modes of ventilation, in moderate ARDS in cirrhosis: A pilot randomized trial.

BACKGROUND: Mechanical ventilation in cirrhosis with acute respiratory distress syndrome (ARDS) is not widely studied. We aimed to study the effect of...

Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors.

In the last year, the COVID-19 pandemic has highly affected the lifestyle of the world population, encouraging the scientific community towards a grea...

Rapid high-quality PET Patlak parametric image generation based on direct reconstruction and temporal nonlocal neural network.

Parametric imaging based on dynamic positron emission tomography (PET) has wide applications in neurology. Compared to indirect methods, direct recons...

Development of novel-nanobody-based lateral-flow immunochromatographic strip test for rapid detection of recombinant human interferon α2b.

Recombinant human interferon α2b (rhIFNα2b) is widely used as an antiviral therapy agent for the treatment of hepatitis B and hepatitis C. The current...

Automated Measurements of Body Composition in Abdominal CT Scans Using Artificial Intelligence Can Predict Mortality in Patients With Cirrhosis.

Body composition measures derived from already available electronic medical records (computed tomography [CT] scans) can have significant value, but a...

Assessment of deep learning-based PET attenuation correction frameworks in the sinogram domain.

This study set out to investigate various deep learning frameworks for PET attenuation correction in the sinogram domain. Different models for both ti...

DeepHBV: a deep learning model to predict hepatitis B virus (HBV) integration sites.

BACKGROUND: The hepatitis B virus (HBV) is one of the main causes of viral hepatitis and liver cancer. HBV integration is one of the key steps in the ...

Optimizing COVID-19 vaccine distribution across the United States using deterministic and stochastic recurrent neural networks.

Optimizing COVID-19 vaccine distribution can help plan around the limited production and distribution of vaccination, particularly in early stages. On...

Orthogonal quantification of soluble inducible T-cell costimulator (ICOS) in healthy and diseased human serum.

Inducible T-cell costimulator (ICOS), a homodimeric protein expressed on the surface of activated T-cells, is being investigated as a potential therap...

Face mask detection using deep learning: An approach to reduce risk of Coronavirus spread.

Effective strategies to restrain COVID-19 pandemic need high attention to mitigate negatively impacted communal health and global economy, with the br...

Deep learning-based framework for the distinction of membranous nephropathy: a new approach through hyperspectral imagery.

BACKGROUND: Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic membranous nephropathy (IMN) and hepatitis B ...

One-step-immunoassay of procalcitonin enables rapid and accurate diagnosis of bacterial infection.

Procalcitonin (PCT) ( a precursor of calcitonin) attracts much attention as a reliable biomarker of bacterial infections because its concentration inc...