Latest AI and machine learning research in dyslipidemia for healthcare professionals.
Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atheroscle...
Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for...
The automated and accurate carotid plaque segmentation in B-mode ultrasound (US) is an essential par...
The clinical characteristics and vascular computed tomography (CT) imaging characteristics of patien...
BACKGROUND AND AIM: L. seeds (TFG) are used as spices in Indian cuisine. In Indian traditional medi...
Carotid ultrasound measurement of total plaque area (TPA) provides a method for quantifying carotid ...
DGAT1 plays a crucial controlling role in triglyceride biosynthetic pathways, which makes it an attr...
Peripheral artery disease is an atherosclerotic disorder which, when present, portends poor patient ...
BACKGROUND AND AIMS: We developed a deep learning (DL) model for automated atherosclerotic plaque ca...
There is not enough information about tinnitus and related parameters in patients with heart failure...
PURPOSE: Coronary artery events are mainly associated with atherosclerosis in adult population, whic...
Few studies have been conducted to classify and predict the influence of nutritional intake on overw...
The current study utilized an artificial neural network (ANN) to generate computational models to ac...
Background An artificial intelligence vessel segmentation tool, Fully Automated and Robust Analysis ...
BACKGROUND: There is no consensus on the best method to estimate Low Density Lipoprotein-Cholesterol...
Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The ...
Premature all-cause mortality is high in patients receiving peritoneal dialysis (PD). The accurate a...
Hyperlipidemia causes diseases like cardiovascular disease, cancer, Type II Diabetes and Alzheimer's...
Biological processes are inherently continuous, and the chance of phenotypic discovery is significan...
Our study investigated the feasibility and clinical relevance of brain age prediction using axial T2...
Predicting the risk of cardiovascular disease is the key to primary prevention. Machine learning has...