Hepatitis

Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals.

Several European countries have established criteria for prioritising initiation of treatment in patients infected with the hepatitis C virus (HCV) by grouping patients according to clinical characteristics. Based on neural network techniques, our objective was to identify those factors for HIV/HCV co-infected patients (to which clinicians have given careful consideration before treatment uptake) ...

Biomarker Localization From Deep Learning Regression Networks.

Biomarker estimation methods from medical images have traditionally followed a segment-and-measure strategy. Deep-learning regression networks have changed such a paradigm, enabling the direct estimation of biomarkers in databases where segmentation masks are not present. While such methods achieve high performance, they operate as a black-box. In this work, we present a novel deep learning networ...

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design of personalized cancer vaccines. Thi...

Machine-learning based patient classification using Hepatitis B virus full-length genome quasispecies from Asian and European cohorts.

Chronic infection with Hepatitis B virus (HBV) is a major risk factor for the development of advanced liver disease including fibrosis, cirrhosis, and...

Body Composition Analysis of Computed Tomography Scans in Clinical Populations: The Role of Deep Learning.

BACKGROUND: Body composition is increasingly being recognized as an important prognostic factor for health outcomes across cancer, liver cirrhosis, an...

The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.

PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vaccine-related anaphylaxis from plain-text clinical n...

Verification with the utility of an established rapid assessment of brain safety for newly developed vaccines.

In the twenty-first century, high contagious infectious diseases such as SARS (Severe Acute Respiratory Syndrome), MERS (Middle East Respiratory Syndr...

A comparison of machine learning techniques for classification of HIV patients with antiretroviral therapy-induced mitochondrial toxicity from those without mitochondrial toxicity.

BACKGROUND: Antiretroviral therapy (ART) has significantly reduced HIV-related morbidity and mortality. However, therapeutic benefit of ART is often l...

Predictors, Presentation, and Treatment Outcomes of Recurrent Hepatocellular Carcinoma After Liver Transplantation: A Large Single Center Experience.

BACKGROUND: Liver transplantation (LT) is an accepted therapeutic option for hepatocellular carcinoma (HCC) in patients with cirrhosis. Despite carefu...

Global Mittag-Leffler stability and synchronization of discrete-time fractional-order complex-valued neural networks with time delay.

Without decomposing complex-valued systems into real-valued systems, this paper investigates existence, uniqueness, global Mittag-Leffler stability an...

Detecting liver fibrosis using a machine learning-based approach to the quantification of the heart-induced deformation in tagged MR images.

Liver disease causes millions of deaths per year worldwide, and approximately half of these cases are due to cirrhosis, which is an advanced stage of ...

Non-invasive diagnosis of non-alcoholic steatohepatitis and fibrosis with the use of omics and supervised learning: A proof of concept study.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 25-30% of the general population and is characterized by the presence of non-alcoholic f...

Peptide arrays incubated with three collections of human sera from patients infected with mosquito-borne viruses.

Global outbreaks caused by emerging or re-emerging arthropod-borne viruses (arboviruses) are becoming increasingly more common. These pathogens inclu...

Hepatitis B surface antigen reduction as a result of switching from long-term entecavir administration to tenofovir.

BACKGROUND AND AIM: Loss of hepatitis B surface antigen (HBsAg) is an important goal in the treatment of chronic hepatitis B. We investigated whether ...

The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system.

Machine learning has the potential to identify novel biological factors underlying successful antibody responses to influenza vaccines. The first atte...

A SEMIPARAMETRIC MODELING APPROACH USING BAYESIAN ADDITIVE REGRESSION TREES WITH AN APPLICATION TO EVALUATE HETEROGENEOUS TREATMENT EFFECTS.

Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and covariat...

Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data.

Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging research. However, direct replication studies and st...

Correlation-Based Ensemble Feature Selection Using Bioinspired Algorithms and Classification Using Backpropagation Neural Network.

A framework for clinical diagnosis which uses bioinspired algorithms for feature selection and gradient descendant backpropagation neural network for ...

The complement system in liver diseases: Evidence-based approach and therapeutic options.

Complement is usually seen to largely originate from the liver to accomplish its tasks systemically - its return to the production site has long been ...

Rheological and physicochemical stability of hydrolyzed jackfruit juice ( L.) processed by spray drying.

Spray drying represents a viable alternative for the stabilization of juice and extract of a great diversity of plant in tropical zones, such as jackf...