Prevention

Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch.

OBJECTIVE: Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common shoulder disorders. However, adherence to these protocols is often poor and typically worse for unsupervised home exercise programs. Currently, there are limited tools available for objective measurement of adherence in the home setting. The goal of th...

Machine learning algorithm-based risk prediction model of coronary artery disease.

In view of high mortality associated with coronary artery disease (CAD), development of an early predicting tool will be beneficial in reducing the burden of the disease. The database comprising demographic, conventional, folate/xenobiotic genetic risk factors of 648 subjects (364 cases of CAD and 284 healthy controls) was used as the basis to develop CAD risk and percentage stenosis prediction mo...

Pump Speed Optimization in Patients Implanted With the HeartMate 3 Device.

BACKGROUND: Pump speed optimization in patients implanted with a ventricular assist device represents a major challenge during the follow-up period. W...

Detraining effects of regular Tai Chi exercise on postural control ability in older women: A randomized controlled trial.

BACKGROUND/OBJECTIVE: This study aimed to investigate the training and detraining effects of Tai Chi (TC) on postural control ability in single leg st...

A comparison of statistical and machine-learning techniques in evaluating the association between dietary patterns and 10-year cardiometabolic risk (2002-2012): the ATTICA study.

Statistical methods are usually applied in examining diet-disease associations, whereas factor analysis is commonly used for dietary pattern recogniti...

Effect of Health and Training on Ultrasensitive Cardiac Troponin in Marathon Runners.

PURPOSE: Cardiac troponin (cTn) is the gold standard biomarker for assessing cardiac damage. Previous studies have demonstrated increases in plasma cT...

Training radial basis function networks for wind speed prediction using PSO enhanced differential search optimizer.

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural net...

Productive performance, egg quality, hematological parameters and serum chemistry of laying hens fed diets supplemented with certain fat-soluble vitamins, individually or combined, during summer season.

This present study aimed to determine the efficacy of supplementing layer diets with vitamin A (0, 8,000 and 16,000 IU/kg diet) and vitamin E (0, 250 ...

Survey of potential receptivity to robotic-assisted exercise coaching in a diverse sample of smokers and nonsmokers.

A prior project found that an intensive (12 weeks, thrice weekly sessions) in-person, supervised, exercise coaching intervention was effective for smo...

Predicting net joint moments during a weightlifting exercise with a neural network model.

The purpose of this study was to develop and train a Neural Network (NN) that uses barbell mass and motions to predict hip, knee, and ankle Net Joint ...

Using machine learning on cardiorespiratory fitness data for predicting hypertension: The Henry Ford ExercIse Testing (FIT) Project.

This study evaluates and compares the performance of different machine learning techniques on predicting the individuals at risk of developing hyperte...

Extracting Healthcare Quality Information from Unstructured Data.

Healthcare quality research is a fundamental task that involves assessing treatment patterns and measuring the associated patient outcomes to identify...

L Extracts against : Antimicrobial activity, antioxidant capacity, hygienic behavior and colony strength.

The aim of this work was to compare the antimicrobial activity against and the antioxidant capacity of two L. extracts obtained by different extract...

Comparative Performance Analysis of Support Vector Machine, Random Forest, Logistic Regression and k-Nearest Neighbours in Rainbow Trout (Oncorhynchus Mykiss) Classification Using Image-Based Features.

The main aim of this study was to develop a new objective method for evaluating the impacts of different diets on the live fish skin using image-based...

Interpretation of biological experiments changes with evolution of the Gene Ontology and its annotations.

Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying...

Development of a New Robotic Ankle Rehabilitation Platform for Hemiplegic Patients after Stroke.

A large amount of hemiplegic survivors are suffering from motor impairment. Ankle rehabilitation exercises act an important role in recovering patient...

Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet.

Computer-based technological innovation provides advancements in sophisticated and diverse analytical instruments, enabling massive amounts of data co...

Boosted neural networks scoring functions for accurate ligand docking and ranking.

Predicting the native poses of ligands correctly is one of the most important steps towards successful structure-based drug design. Binding affinities...

Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The ...

Meta-Analysis of Expression Datasets: Comparing Virus Infection and Blood-Fed Transcriptomes to Identify Markers of Virus Presence.

The mosquito (L.) is vector of several arboviruses including dengue, yellow fever, chikungunya, and more recently zika. Previous transcriptomic studi...