This study evaluates and compares the performance of different machine learning techniques on predicting the individuals at risk of developing hypertension, and who are likely to benefit most from interventions, using the cardiorespiratory fitness da...
In recent years, human activity recognition from body sensor data or wearable sensor data has become a considerable research attention from academia and health industry. This research can be useful for various e-health applications such as monitoring...
Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme
Dec 20, 2017
The current study aims to identify if mouth rinsing with a 6% carbohydrate mouth-rinse (CMR) solution and mouth rinsing and ingestion of caffeine (CMR+CAFF) can affect exercise performance during steady-state (SS) running and high-intensity intervals...
Research quarterly for exercise and sport
Dec 20, 2017
PURPOSE: The purpose of this study was to examine differences in heart rate recovery (HRRec) and oxygen consumption recovery (VO recovery) between young healthy-weight children and children with obesity following a maximal volitional graded exercise ...
BMC medical informatics and decision making
Dec 19, 2017
BACKGROUND: Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into p...
BACKGROUND: It is widely recognized that overt hyper- as well as hypothyroidism are potential causes of heart failure (HF). Additionally it has been recently reported that subclinical hypothyroidism (sub-hypo) is associated with atherosclerosis, deve...
BACKGROUND: The objective was to better understand Doppler hemodynamics and exercise capacity in patients with Fontan palliation by delineating the hemodynamic mechanism for temporal changes in their peak oxygen consumption (V̇o).
OBJECTIVES: This study evaluated the added predictive value of combining clinical information and myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) data using machine learning (ML) to predict major adverse cardiac ...
Previous studies have demonstrated that cardiorespiratory fitness is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined ca...
Rehabilitation of human motor function is an issue of growing significance, and human-interactive robots offer promising potential to meet the need. For the lower extremity, however, robot-aided therapy has proven challenging. To inform effective app...
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