COVID-19

A Real-Time Arrhythmia Heartbeats Classification Algorithm Using Parallel Delta Modulations and Rotated Linear-Kernel Support Vector Machines.

Real-time wearable electrocardiogram monitoring sensor is one of the best candidates in assisting cardiovascular disease diagnosis. In this paper, we present a novel real-time machine learning system for Arrhythmia classification. The system is based on the parallel Delta modulation and QRS/PT wave detection algorithms. We propose a patient dependent rotated linear-kernel support vector machine cl...

Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease.

A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here, we introduce a unified population-genetic and machine-learning model, called inear llele-pecific election nferenc (), for estimating the fitness effects of all observed and potential single-nucleotide variants, based on polymorphism data and predictive genomic fea...

Block Forests: random forests for blocks of clinical and omics covariate data.

BACKGROUND: In the last years more and more multi-omics data are becoming available, that is, data featuring measurements of several types of omics da...

Incorporating Conversational Strategies in a Social Robot to Interact with People with Dementia.

BACKGROUND: Socially assistive robots (SARs) have the potential to assist nonpharmacological interventions based on verbal communication to support th...

Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network.

An accurate prediction of achievable dose distribution on a patient specific basis would greatly improve IMRT/VMAT planning in both efficiency and qua...

A new M23-based ELISA assay for anti-aquaporin 4 autoantibodies: diagnostic accuracy and clinical correlation.

PURPOSE: Although many assays have been developed to detect anti-aquaporin-4 (AQP4) antibodies, most of these assays require sophisticated techniques ...

Detecting mitotic cells in HEp-2 images as anomalies via one class classifier.

We propose a novel framework for classification of mitotic v/s non-mitotic cells in a Computer Aided Diagnosis (CAD) system for Anti-Nuclear Antibodie...

Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss.

Knee osteoarthritis (OA) is one major cause of activity limitation and physical disability in older adults. Early detection and intervention can help ...

Using Machine Learning Algorithms to Predict Hepatitis B Surface Antigen Seroclearance.

Hepatitis B surface antigen (HBsAg) seroclearance during treatment is associated with a better prognosis among patients with chronic hepatitis B (CHB)...

A machine-learning approach for accurate detection of copy number variants from exome sequencing.

Copy number variants (CNVs) are a major cause of several genetic disorders, making their detection an essential component of genetic analysis pipeline...

A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation.

Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells. Here, we use deep learning to predict APA from DNA sequ...

Seroprevalence of antibodies for pertussis and diphtheria among people leaving or entering China: a cross-sectional study.

INTRODUCTION: Despite high population immunity, pertussis remains one of the leading causes of vaccine-preventable deaths worldwide. The aim of this s...

Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis.

BACKGROUND: The propensity of different Anopheles mosquitoes to bite humans instead of other vertebrates influences their capacity to transmit pathoge...

A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures.

Recurrent neural networks (RNNs) have been widely adopted in research areas concerned with sequential data, such as text, audio, and video. However, R...

Machine learning in the clinical and language characterisation of primary progressive aphasia variants.

INTRODUCTION: Primary progressive aphasia (PPA) is a clinical syndrome of neurodegenerative origin with 3 main variants: non-fluent, semantic, and log...

Deep neural network concepts for background subtraction:A systematic review and comparative evaluation.

Conventional neural networks have been demonstrated to be a powerful framework for background subtraction in video acquired by static cameras. Indeed,...

Diagnostic ability of artificial intelligence using deep learning analysis of cyst fluid in differentiating malignant from benign pancreatic cystic lesions.

The diagnosis of pancreatic cystic lesions remains challenging. This study aimed to investigate the diagnostic ability of carcinoembryonic antigen (CE...

BoSR: A CNN-based aurora image retrieval method.

The deep learning models especially the CNN have achieved amazing performance on natural image retrieval. However, remote sensing images captured with...

Emotion classification using a CNN_LSTM-based model for smooth emotional synchronization of the humanoid robot REN-XIN.

In this paper, we propose an Emotional Trigger System to impart an automatic emotion expression ability within the humanoid robot REN-XIN, in which th...

Machine learning-assisted directed protein evolution with combinatorial libraries.

To reduce experimental effort associated with directed protein evolution and to explore the sequence space encoded by mutating multiple positions simu...