Cardiovascular

Metabolic Syndrome

Latest AI and machine learning research in metabolic syndrome for healthcare professionals.

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Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification.

Blood pressure is a basic physiological parameter in the cardiovascular circulatory system. Long-ter...

Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes.

OBJECTIVE: Metformin is the preferred first-line medication for management of type 2 diabetes and pr...

High triglycerides to HDL-cholesterol ratio is associated with insulin resistance in normal-weight healthy adults.

AIM: To evaluate the association between high triglyceride/HDL-cholesterol (TG/HDL-C) ratio and insu...

Endothelium-independent and calcium channel-dependent relaxation of the porcine cerebral artery by different species and strains of turmeric.

OBJECTIVE: To clarify the underlying mechanism of turmeric, which is traditionally used as a medicin...

Quantification of the constituents of the traditional Korea medicine, Samryeongbaekchul-san, and assessment of its antiadipogenic effect.

Samryeongbaekchul-san (SBS) is a traditional herbal formula, which is used for the treatment of dysp...

Fibroblast growth factor23 is associated with axonal integrity and neural network architecture in the human frontal lobes.

Elevated levels of FGF23 in individuals with chronic kidney disease (CKD) are associated with advers...

Effect of daily intake of a low-alcohol orange beverage on cardiovascular risk factors in hypercholesterolemic humans.

Oxidative stress, inflammation status, endothelial dysfunction, and imbalanced lipid metabolism play...

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...

Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension.

PURPOSE OF REVIEW: Evidence that artificial intelligence (AI) is useful for predicting risk factors ...

Machine Learning Helps Identify New Drug Mechanisms in Triple-Negative Breast Cancer.

This paper demonstrates the ability of mach- ine learning approaches to identify a few genes among t...

Plasminogen activator inhibitor-1 is associated with the metabolism and development of advanced colonic polyps.

Implications of plasminogen activator inhibitor-1 (PAI-1) in colonic polyps remain elusive. A prospe...

Factors associated with dementia in elderly.

We analyzed the factors associated with dementia in the elderly attended at a memory outpatient clin...

Mechanism & inhibition kinetics of bioassay-guided fractions of Indian medicinal plants and foods as ACE inhibitors.

Hypertension is a becoming a major threat to the world. Angiotensin converting enzyme (ACE) is a key...

Using machine learning on cardiorespiratory fitness data for predicting hypertension: The Henry Ford ExercIse Testing (FIT) Project.

This study evaluates and compares the performance of different machine learning techniques on predic...

Extracting Healthcare Quality Information from Unstructured Data.

Healthcare quality research is a fundamental task that involves assessing treatment patterns and mea...

Pharmacological therapy selection of type 2 diabetes based on the SWARA and modified MULTIMOORA methods under a fuzzy environment.

Medication selection for Type 2 Diabetes (T2D) is a challenging medical decision-making problem invo...

A Systematic Machine Learning Based Approach for the Diagnosis of Non-Alcoholic Fatty Liver Disease Risk and Progression.

Prevention and diagnosis of NAFLD is an ongoing area of interest in the healthcare community. Screen...

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