AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Exercise Test

Showing 61 to 70 of 138 articles

Clear Filters

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

Transplantation proceedings
BACKGROUND: Pump speed optimization in patients implanted with a ventricular assist device represents a major challenge during the follow-up period. We present our findings on whether combined invasive hemodynamic ramp tests and cardiopulmonary exerc...

Noninvasive prediction of Blood Lactate through a machine learning-based approach.

Scientific reports
We hypothesized that blood lactate concentration([Lac]) is a function of cardiopulmonary variables, exercise intensity and some anthropometric elements during aerobic exercise. This investigation aimed to establish a mathematical model to estimate [L...

Contribution of Cardiovascular Reserve to Prognostic Categories of Heart Failure With Preserved Ejection Fraction: A Classification Based on Machine Learning.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: The authors used cluster analysis of data from cardiovascular domains associated with exercise intolerance to help define prognostic phenotypes of patients with heart failure with preserved ejection fraction (HFpEF).

Human electrocortical dynamics while stepping over obstacles.

Scientific reports
To better understand human brain dynamics during visually guided locomotion, we developed a method of removing motion artifacts from mobile electroencephalography (EEG) and studied human subjects walking and running over obstacles on a treadmill. We ...

Expert-level classification of ventilatory thresholds from cardiopulmonary exercising test data with recurrent neural networks.

European journal of sport science
First and second ventilatory thresholds (VT and VT) represent the boundaries of the moderate-heavy and heavy-severe exercise intensity. Currently, VTs are primarily detected visually from cardiopulmonary exercise test (CPET) data, beginning with an i...

On the interpretability of machine learning-based model for predicting hypertension.

BMC medical informatics and decision making
BACKGROUND: Although complex machine learning models are commonly outperforming the traditional simple interpretable models, clinicians find it hard to understand and trust these complex models due to the lack of intuition and explanation of their pr...

Automation of the Timed-Up-and-Go Test Using a Conventional Video Camera.

IEEE journal of biomedical and health informatics
The Timed-Up-and-Go (TUG) test is a simple clinical tool commonly used to quickly assess the mobility of patients. Researchers have endeavored to automate the test using sensors or motion tracking systems to improve its accuracy and to extract more r...

Clinical effects of robot-assisted gait training and treadmill training for Parkinson's disease. A randomized controlled trial.

Annals of physical and rehabilitation medicine
BACKGROUND: Although gait disorders strongly contribute to perceived disability in people with Parkinson's disease, clinical trials have failed to identify which task-oriented gait training method can provide the best benefit. Freezing of gait remain...