Exercise & Fitness

Is P&T Ready to Add Rapid Cycle Analytics to Formulary?

The intent of this article is to evaluate a novel approach, using rapid cycle analytics and real world evidence, to optimize and improve the medication evaluation process to help the formulary decision making process, while reducing time for clinicians. The Pharmacy and Therapeutics (P&T) Committee within each health system is responsible for evaluating medication requests for formulary addition...

Rehabilitation of older people with Parkinson's disease: an innovative protocol for RCT study to evaluate the potential of robotic-based technologies.

BACKGROUND: Parkinson's disease is one of the most frequent causes of disability among the older adults. It is a chronic-progressive neuro-degenerative disease, characterized by several motor disorders. Balance disorders are a symptom that involves the body axis and do not respond to dopaminergic therapy used in Parkinson's disease. Therefore, physiotherapy becomes an important intervention for th...

Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, econo...

Automated classification of cells into multiple classes in epithelial tissue of oral squamous cell carcinoma using transfer learning and convolutional neural network.

The analysis of tissue of a tumor in the oral cavity is essential for the pathologist to ascertain its grading. Recent studies using biopsy images rev...

Measurement and identification of mental workload during simulated computer tasks with multimodal methods and machine learning.

This study attempted to multimodally measure mental workload and validate indicators for estimating mental workload. A simulated computer work compose...

Reaching exercise for chronic paretic upper extremity after stroke using a novel rehabilitation robot with arm-weight support and concomitant electrical stimulation and vibration: before-and-after feasibility trial.

BACKGROUND: Our group developed a rehabilitation robot to assist with repetitive, active reaching movement of a paretic upper extremity. The robot is ...

Applying machine learning methods to develop a successful aging maintenance prediction model based on physical fitness tests.

AIM: The purpose of this study was to develop a machine learning prediction model for successful aging (SA) based on physical fitness tests.

Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images.

Knee Osteoarthritis (OA) is a common musculoskeletal disorder in the United States. When diagnosed at early stages, lifestyle interventions such as ex...

Deep Learning to Unveil Correlations between Urban Landscape and Population Health.

The global healthcare landscape is continuously changing throughout the world as technology advances, leading to a gradual change in lifestyle. Severa...

Three-dimensional modelling of wheelchair contrived with lower limb exoskeleton for right hemiplegic dysfunction.

Hemiplegia is a type of paralysis that affects one side of the body due to stroke, characterizing severe weakness or rigid movement. Many people of di...

Improving energy expenditure estimates from wearable devices: A machine learning approach.

A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a ...

Unraveling the Mysteries of Motivation.

Motivation plays a central role in human behavior and cognition but is not well captured by widely used artificial intelligence (AI) and computational...

Augmented Performance Feedback during Robotic Gait Therapy Results in Moderate Intensity Cardiovascular Exercise in Subacute Stroke.

BACKGROUND: Low cardiovascular fitness is common poststroke. Conventional subacute stroke rehabilitation does not meet Australian National Stroke Guid...

Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults.

The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Inde...

Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset.

Drug-induced liver injury (DILI) remains one of the challenges in the safety profile of both authorized and candidate drugs, and predicting hepatotoxi...

Prediction of admission in pediatric emergency department with deep neural networks and triage textual data.

Emergency department (ED) overcrowding is a global condition that severely worsens attention to patients, increases clinical risks and affects hospita...

Estimating an individual's oxygen uptake during cycling exercise with a recurrent neural network trained from easy-to-obtain inputs: A pilot study.

Measurement of oxygen uptake during exercise ([Formula: see text]) is currently non-accessible to most individuals without expensive and invasive equi...

Retrospective Cohort Analysis from a High-Volume Center of Prognostic Factors Affecting Biochemical Relapse in Patients with Encapsulated, Margin-Negative, Isolated Seminal Vesicle Invasion After Robot-Assisted Laparoscopic Prostatectomy: A Novel Study.

Specimen pathology findings collectively impact the long-term outcomes of robot-assisted laparoscopic prostatectomy. Since seminal vesicle invasion (...

Nanotoxicology data for tools: a literature review.

The exercise of non-testing approaches in nanoparticles (NPs) hazard assessment is necessary for the risk assessment, considering cost and time effici...

Exercise cardiac power and the risk of heart failure in men: A population-based follow-up study.

BACKGROUND: Little is known about exercise cardiac power (ECP), defined as the ratio of directly measured maximal oxygen uptake with peak systolic blo...