Cardiovascular

Prevention

Latest AI and machine learning research in prevention for healthcare professionals.

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Showing 169-189 of 11,961 articles
Machine learning uncovers manganese as a key nutrient associated with reduced risk of steatotic liver disease.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 2...

Tai Chi Expertise Classification in Older Adults Using Wrist Wearables and Machine Learning.

Tai Chi is a Chinese martial art that provides an adaptive and accessible exercise for older adults ...

Predicting angiographic coronary artery disease using machine learning and high-frequency QRS.

AIM: Exercise stress ECG is a common diagnostic test for stable coronary artery disease, but its sen...

Decoding lower-limb kinematic parameters during pedaling tasks using deep learning approaches and EEG.

Stroke is a neurological condition that usually results in the loss of voluntary control of body mov...

Machine Learning for Movement Pattern Changes during Kinect-Based Mixed Reality Exercise Programs in Women with Possible Sarcopenia: Pilot Study.

BACKGROUND: Sarcopenia is a muscle-wasting condition that affects older individuals. It can lead to ...

The Application of Robotics in Cardiac Rehabilitation: A Systematic Review.

: Robotics is commonly used in the rehabilitation of neuro-musculoskeletal injuries and diseases. Wh...

Effect of dexamethasone pretreatment using deep learning on the surgical effect of patients with gastrointestinal tumors.

To explore the application efficacy and significance of deep learning in anesthesia management for g...

[Medicine of the future: the role of artificial intelligence in optimizing nutrition for the health of the Russian population].

One of the most pressing medical, social and government tasks is to ensure health saving, improve th...

Evaluation of online chat-based artificial intelligence responses about inflammatory bowel disease and diet.

INTRODUCTION: The USA has the highest age-standardized prevalence of inflammatory bowel disease (IBD...

Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.

Peptide-based drug discovery has surged with the development of peptide hormone-derived analogs for ...

Artificial Intelligence in Urology: Application of a Machine Learning Model to Predict the Risk of Urolithiasis in a General Population.

This research presents our application of artificial intelligence (AI) in predicting urolithiasis ri...

Machine learning predicts peak oxygen uptake and peak power output for customizing cardiopulmonary exercise testing using non-exercise features.

PURPOSE: Cardiopulmonary exercise testing (CPET) is considered the gold standard for assessing cardi...

Predicting long-term sleep deprivation using wearable sensors and health surveys.

Sufficient sleep is essential for individual well-being. Inadequate sleep has been shown to have sig...

Multilayer Perceptron-Based Wearable Exercise-Related Heart Rate Variability Predicts Anxiety and Depression in College Students.

(1) Background: This study aims to investigate the correlation between heart rate variability (HRV) ...

The Role of Artificial Intelligence in Nutrition Research: A Scoping Review.

Artificial intelligence (AI) refers to computer systems doing tasks that usually need human intellig...

AI nutrition recommendation using a deep generative model and ChatGPT.

In recent years, major advances in artificial intelligence (AI) have led to the development of power...

Identifying the risk of exercises, recommended by an artificial intelligence for patients with musculoskeletal disorders.

Musculoskeletal disorders (MSDs) impact people globally, cause occupational illness and reduce produ...

A machine learning (ML) approach to understanding participation in government nutrition programs.

Machine Learning (ML) affords researchers tools to advance beyond research methods commonly employed...

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