Cardiovascular

Dyslipidemia

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

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The Role of Chronic Renal Disease on the Linking Obesity/Hypertension.

Obesity is accompanied by several disorders. This study investigated the role of chronic renal disea...

Kidney dysfunction and oxidative stress in doxorubicin-induced nephrotic rat: Protective role of sesame oil.

Doxorubicin (DOX) is an antineoplastic agent which it's clinical use has been limited due to its maj...

Colorectal Cancer Detected by Machine Learning Models Using Conventional Laboratory Test Data.

Current diagnostic methods for colorectal cancer (CRC) are colonoscopy and sigmoidoscopy, which are...

Detection of Asymptomatic Carotid Artery Stenosis in High-Risk Individuals of Stroke Using a Machine-Learning Algorithm.

Objective Asymptomatic carotid stenosis (ACS) is closely associated to the incidence of severe cereb...

Correlation between Immune-Inflammatory Markers and Clinical Features in Patients with Acute Ischemic Stroke.

OBJECTIVE: Chronic inflammatory processes involving the vascular wall may induce atherosclerosis. Im...

Rhabdomyolysis in a Civil Aviation Pilot.

Rhabdomyolysis is a potentially fatal disease caused by trauma, infections, and toxins. Rhabdomyoly...

Machine Learning Improves Cardiovascular Risk Definition for Young, Asymptomatic Individuals.

BACKGROUND: Clinical practice guidelines recommend assessment of subclinical atherosclerosis using i...

Prediction of atherosclerotic disease progression combining computational modelling with machine learning.

Non-invasive serial computed tomography coronary angiography (CTCA) was acquired from 32 patients an...

A deep learning oriented method for automated 3D reconstruction of carotid arterial trees from MR imaging.

The scope of this paper is to present a new carotid vessel segmentation algorithm implementing the U...

Locate the Superficial Femoral Artery with Occlusion by Deep Neural Network Correcting Interpolation.

In clinical practice, doctors usually use computed tomography angiography (CTA) to examine lower ext...

Automated interpretation of the coronary angioscopy with deep convolutional neural networks.

BACKGROUND: Coronary angioscopy (CAS) is a useful modality to assess atherosclerotic changes, but in...

Machine learning reveals serum sphingolipids as cholesterol-independent biomarkers of coronary artery disease.

BACKGROUNDCeramides are sphingolipids that play causative roles in diabetes and heart disease, with ...

Potassium selenocyanoacetate reduces the blood triacylglycerol and atherosclerotic plaques in high-fat-dieted mice.

BACKGROUND: Controlling blood lipid levels at the early stage of cardiovascular disease is a major f...

Motion-compensated frame rate up-conversion in carotid ultrasound images using optical flow and manifold learning.

OBJECTIVE: Carotid ultrasonography is a reliable and non-invasive method to evaluate atherosclerosis...

Ex-vivo antihypertensive and calcium channel blocking activity of Androsace foliosa n-hexane leaves fraction on isolated rabbit aorta.

Hypertension is persistent elevation in blood pressure for 3-4 weeks. Estimated global prevalence of...

Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH...

Sarcopenia feature selection and risk prediction using machine learning: A cross-sectional study.

The purpose of this study was to verify the usefulness of machine learning (ML) for selection of ris...

Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA.

Background We developed a new left ventricular hypertrophy ( LVH ) criterion using a machine-learnin...

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