Cardiovascular

Prevention

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

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Myoelectric control algorithm for robot-assisted therapy: a hardware-in-the-loop simulation study.

BACKGROUND: A direct blow to the knee is one way to injure the anterior cruciate ligament (ACL), e.g...

Protective effects of Ganoderma triterpenoids on cadmium-induced oxidative stress and inflammatory injury in chicken livers.

Several studies have been conducted on liver damage caused by cadmium, but few on the protective eff...

Exploring the interactions between serum free fatty acids and fecal microbiota in obesity through a machine learning algorithm.

Serum free fatty acids (FFA) are generally elevated in obesity. The gut microbiota is involved in th...

Effects of a cyborg-type robot suit HAL on cardiopulmonary burden during exercise in normal subjects.

BACKGROUND: The hybrid assistive limb (HAL) is the world's first cyborg-type robot suit that provide...

Blood Sugar Level Indication Through Chewing and Swallowing from Acoustic MEMS Sensor and Deep Learning Algorithm for Diabetic Management.

Diabetes, a metabolic disorder due to high blood glycemic index in the human body. The glycemic inde...

Could Robots Help Older People with Age-Related Nutritional Problems? Opinions of Potential Users.

The rapid development of new technologies has recently raised interest in the use of assistive robo...

A multi-strain probiotic administered via drinking water enhances feed conversion efficiency and meat quality traits in indigenous chickens.

Whereas the use of probiotics is commonplace in commercial production of improved chicken strains, l...

Social and nutritional factors shape larval aggregation, foraging, and body mass in a polyphagous fly.

The majority of insect species have a clearly defined larval stage during development. Larval nutrit...

Deep learning-based quantification of abdominal fat on magnetic resonance images.

Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, ...

Wearable Sensor Data to Track Subject-Specific Movement Patterns Related to Clinical Outcomes Using a Machine Learning Approach.

Wearable sensors can provide detailed information on human movement but the clinical impact of this ...

Designing robot-assisted neurorehabilitation strategies for people with both HIV and stroke.

There is increasing evidence that HIV is an independent risk factor for stroke, resulting in an emer...

Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.

BACKGROUND: The risk factors of diabetic retinopathy (DR) were investigated extensively in the past ...

Cardiac Phase Space Tomography: A novel method of assessing coronary artery disease utilizing machine learning.

BACKGROUND: Artificial intelligence (AI) techniques are increasingly applied to cardiovascular (CV) ...

Use of Deep Learning to Examine the Association of the Built Environment With Prevalence of Neighborhood Adult Obesity.

IMPORTANCE: More than one-third of the adult population in the United States is obese. Obesity has b...

Incorporating Unannounced Meals and Exercise in Adaptive Learning of Personalized Models for Multivariable Artificial Pancreas Systems.

BACKGROUND: Despite the recent advancements in the modeling of glycemic dynamics for type 1 diabetes...

Behavioral Modeling in Weight Loss Interventions.

Designing systems with human agents is difficult because it often requires models that characterize ...

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 ...

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 pre...

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