Metabolic Syndrome

Using Machine Learning to Evaluate the Role of Microinflammation in Cardiovascular Events in Patients With Chronic Kidney Disease.

BACKGROUND: Lipid metabolism disorder, as one major complication in patients with chronic kidney disease (CKD), is tied to an increased risk for cardiovascular disease (CVD). Traditional lipid-lowering statins have been found to have limited benefit for the final CVD outcome of CKD patients. Therefore, the purpose of this study was to investigate the effect of microinflammation on CVD in statin-tr...

Artificial intelligence approaches to the determinants of women's vaginal dryness using general hospital data.

The aim of this study is to analyse the determinants of women's vaginal dryness using machine learning. Data came from Korea University Anam Hospital in Seoul, Republic of Korea, with 3298 women, aged 40-80 years, who attended their general health check from January 2010 to December 2012. Five machine learning methods were applied and compared for the prediction of vaginal dryness, measured by a M...

Rhabdomyolysis: An evidence-based approach.

A 76-year-old lady was found on the floor following a fall at home. She was uninjured, but unable to get up, and had been lying on the floor for rough...

Attenuation of Oxidative Stress, Interleukin-6, High-Sensitivity C-Reactive Protein, Plasminogen Activator Inhibitor-1, and Fibrinogen with Oral Vitamin D Supplementation in Patients with T2DM having Vitamin D Deficiency.

 Type 2 diabetes mellitus (T2DM) associated with oxidative stress and inflammation causes endothelial dysfunction, which promotes cardiovascular risk...

Multi-step ahead predictive model for blood glucose concentrations of type-1 diabetic patients.

Continuous monitoring of blood glucose (BG) levels is a key aspect of diabetes management. Patients with Type-1 diabetes (T1D) require an effective to...

A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework.

BACKGROUND: Early and automated detection of carotid plaques prevents strokes, which are the second leading cause of death worldwide according to the ...

A Multilayer Perceptron Neural Network Model to Classify Hypertension in Adolescents Using Anthropometric Measurements: A Cross-Sectional Study in Sarawak, Malaysia.

This study outlines and developed a multilayer perceptron (MLP) neural network model for adolescent hypertension classification focusing on the use of...

Phytogenic compounds from avocado ( L.) extracts; antioxidant activity, amylase inhibitory activity, therapeutic potential of type 2 diabetes.

Diabetes is a worldwide public health disease. Currently, the most effective way to treat diabetes is to mitigate postprandial hyperglycemia by inhibi...

Risk Factors of Restroke in Patients with Lacunar Cerebral Infarction Using Magnetic Resonance Imaging Image Features under Deep Learning Algorithm.

This study was aimed to explore the magnetic resonance imaging (MRI) image features based on the fuzzy local information C-means clustering (FLICM) im...

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study.

INTRODUCTION: Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postn...

Circulating Levels of Endothelin-1 and Big Endothelin-1 in Patients with Essential Hypertension.

The role of endothelin-1 (ET-1) in the pathogenesis of hypertension (HTN) is not clearly established. There is evidence that its circulating levels ar...

Machine learning predictive models of LDL-C in the population of eastern India and its comparison with directly measured and calculated LDL-C.

BACKGROUND: LDL-C is a strong risk factor for cardiovascular disorders. The formulas used to calculate LDL-C showed varying performance in different p...

Diagnostic test accuracy of artificial intelligence analysis of cross-sectional imaging in pulmonary hypertension: a systematic literature review.

OBJECTIVES: To undertake the first systematic review examining the performance of artificial intelligence (AI) applied to cross-sectional imaging for ...

Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods.

Identification of medical conditions using claims data is generally conducted with algorithms based on subject-matter knowledge. However, these claims...

Predicting the Risk of Hypertension Based on Several Easy-to-Collect Risk Factors: A Machine Learning Method.

Hypertension is a widespread chronic disease. Risk prediction of hypertension is an intervention that contributes to the early prevention and manageme...

Hyperglycemia Identification Using ECG in Deep Learning Era.

A growing number of smart wearable biosensors are operating in the medical IoT environment and those that capture physiological signals have received ...

Gallstone Disease in Cirrhosis-Pathogenesis and Management.

Gallstones are more common in patients with cirrhosis of the liver, and the incidence increases with severity of liver disease. Pigment stones are the...

Identifying the predictive effectiveness of a genetic risk score for incident hypertension using machine learning methods among populations in rural China.

Current studies have shown the controversial effect of genetic risk scores (GRSs) in hypertension prediction. Machine learning methods are used extens...

Vaso reactivity test using inhaled nitric oxide for pulmonary arterial hypertension accompanied by severe interstitial lung disease attributed to systemic sclerosis: A case report.

A 70-year-old man with severe interstitial pneumonia attributed to limited cutaneous systemic sclerosis was referred to our institution because of wor...

Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review.

BACKGROUND: Artificial intelligence (AI) has served humanity in many applications since its inception. Currently, it dominates the imaging field-in pa...