COVID-19

Love Wave Sensor for Prostate-Specific Membrane Antigen Detection Based on Hydrophilic Molecularly-Imprinted Polymer.

Prostate-specific membrane antigen (PSMA) is a biomarker for prostate cancer (PCa), and a specific and reliable detection technique of PSMA is urgently required for PCa early diagnosis. A Love wave sensor has been widely studied for real-time sensing and highly sensitive applications, but the sensing unit needs special handling for selective detection purpose. In this study, we prepared a versatil...

High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels.

PURPOSE: The aim of this study was to use machine learning to predict abdominal recurrence on CT on the basis of serial cancer antigen 125 (CA125) levels in patients with advanced high-grade serous ovarian cancer on surveillance.

Experimental Comparisons of Sparse Dictionary Learning and Independent Component Analysis for Brain Network Inference From fMRI Data.

In this work, we conduct comprehensive comparisons between four variants of independent component analysis (ICA) methods and three variants of sparse ...

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an im...

Ecological Vulnerability Assessment Based on Fuzzy Analytical Method and Analytic Hierarchy Process in Yellow River Delta.

The Yellow River Delta (YRD), located in Yellow River estuary, is characterized by rich ecological system types, and provides habitats or migration st...

A hierarchical clustering method for dimension reduction in joint analysis of multiple phenotypes.

Genome-wide association studies (GWAS) have become a very effective research tool to identify genetic variants of underlying various complex diseases....

An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential.

Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Ly...

Spoken language identification based on the enhanced self-adjusting extreme learning machine approach.

Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data ...

A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing.

BACKGROUND: Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is ...

Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature.

BACKGROUND: Automatic identification of term variants or acceptable alternative free-text terms for gene and protein names from the millions of biomed...

Emotion computing using Word Mover's Distance features based on Ren_CECps.

In this paper, we propose an emotion separated method(SeTF·IDF) to assign the emotion labels of sentences with different values, which has a better vi...

Antibody response to 13-valent pneumococcal conjugate vaccine is not impaired in patients with rheumatoid arthritis or primary Sjögren's syndrome without disease modifying treatment.

BACKGROUND: Pneumococcal vaccination is recommended to patients with rheumatoid arthritis (RA) and primary Sjögren's syndrome (pSS). However, little i...

Prevalence and genotypes of Giardia lamblia from stray dogs and cats in Guangdong, China.

Giardia lamblia is a worldwide zoonotic intestinal parasite that infects humans and a wide range of mammals including dogs and cats, causing giardiasi...

Market penetration of intersection AEB: Characterizing avoided and residual straight crossing path accidents.

Car occupants account for one third of all junction fatalities in the European Union. Driver warning can reduce intersection accidents by up to 50 per...

Bayesian convolutional neural network based MRI brain extraction on nonhuman primates.

Brain extraction or skull stripping of magnetic resonance images (MRI) is an essential step in neuroimaging studies, the accuracy of which can severel...

Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Her...

A hidden Markov tree model for testing multiple hypotheses corresponding to Gene Ontology gene sets.

BACKGROUND: Testing predefined gene categories has become a common practice for scientists analyzing high throughput transcriptome data. A systematic ...

Electroencephalographic derived network differences in Lewy body dementia compared to Alzheimer's disease patients.

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) require differential management despite presenting with symptomatic overlap. Currently, t...

Design and validation of an ontology-driven animal-free testing strategy for developmental neurotoxicity testing.

Developmental neurotoxicity entails one of the most complex areas in toxicology. Animal studies provide only limited information as to human relevance...

Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning.

We present a cost-effective and portable platform based on contact lenses for noninvasively detecting Staphylococcus aureus, which is part of the huma...