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UPLC-MS/MS method for the simultaneous quantification of sofosbuvir, sofosbuvir metabolite (GS-331007) and daclatasvir in plasma of HIV/HCV co-infected patients.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Direct-acting antiviral agents (DAAs) represent the major advance in hepatitis C virus (HCV) infection treatment leading to extremely high eradication rates in HCV mono- and HIV/HCV co-infected patients. In this scenery, availability of Therapeutic D...

Learning a variational network for reconstruction of accelerated MRI data.

Magnetic resonance in medicine
PURPOSE: To allow fast and high-quality reconstruction of clinical accelerated multi-coil MR data by learning a variational network that combines the mathematical structure of variational models with deep learning.

A rapid and sensitive supercritical fluid chromatography/tandem mass spectrometry method for detection of ezetimibein dog plasma and its application in pharmacokinetic studies.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
The aim of this study is to develop and validate a rapid, high-selective and sensitive supercritical fluid chromatography/tandem mass spectrometry (SFC-MS/MS) with a multiple reactions monitoring (MRM) mode method for the detection of ezetimibe in do...

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations.

Drug development and industrial pharmacy
This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was...

Developing a dengue forecast model using machine learning: A case study in China.

PLoS neglected tropical diseases
BACKGROUND: In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine lea...

Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

Food research international (Ottawa, Ont.)
In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by do...

The effectiveness of robotic training depends on motor task characteristics.

Experimental brain research
Previous research suggests that the effectiveness of robotic training depends on the motor task to be learned. However, it is still an open question which specific task's characteristics influence the efficacy of error-modulating training strategies....

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

Environmental health : a global access science source
BACKGROUND: There is growing concern of health effects of exposure to pollutant mixtures. We initially proposed an Environmental Risk Score (ERS) as a summary measure to examine the risk of exposure to multi-pollutants in epidemiologic research consi...

Distant Supervision with Transductive Learning for Adverse Drug Reaction Identification from Electronic Medical Records.

Journal of healthcare engineering
Information extraction and knowledge discovery regarding adverse drug reaction (ADR) from large-scale clinical texts are very useful and needy processes. Two major difficulties of this task are the lack of domain experts for labeling examples and int...