Cardiovascular

Dyslipidemia

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

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Showing 358-378 of 4,902 articles
Lipoprotein-associated phospholipase A2 and carotid intima-media thickness in primary Sjögren syndrome.

OBJECTIVES: This study aims to evaluate serum lipoprotein-associated phospholipase A2 (Lp-PLA2) leve...

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 calcula...

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 ...

Ultrasound Image Features under Deep Learning in Breast Conservation Surgery for Breast Cancer.

This study was to analyze the effect of the combined application of deep learning technology and ult...

Gallstone Disease in Cirrhosis-Pathogenesis and Management.

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

Exploring the diagnostic effectiveness for myocardial ischaemia based on CCTA myocardial texture features.

BACKGROUND: To explore the characteristics of myocardial textures on coronary computed tomography an...

The effect of consuming different proportions of hummer fish on biochemical and histopathological changes of hyperglycemic rats.

Hammour fish (grouper fish) are known to be of great nutritional value for human consumption, as the...

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 inceptio...

Multilevel Strip Pooling-Based Convolutional Neural Network for the Classification of Carotid Plaque Echogenicity.

Carotid plaque echogenicity in ultrasound images has been found to be closely correlated with the ri...

Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atheroscle...

Hybrid deep learning segmentation models for atherosclerotic plaque in internal carotid artery B-mode ultrasound.

The automated and accurate carotid plaque segmentation in B-mode ultrasound (US) is an essential par...

Computed Tomography Angiography under Deep Learning in the Treatment of Atherosclerosis with Rapamycin.

The clinical characteristics and vascular computed tomography (CT) imaging characteristics of patien...

Prophylactic effect of . seed extract on inflammatory markers and histopathological changes in high-fat-fed ovariectomized rats.

BACKGROUND AND AIM: L. seeds (TFG) are used as spices in Indian cuisine. In Indian traditional medi...

Deep Learning-Based Carotid Plaque Segmentation from B-Mode Ultrasound Images.

Carotid ultrasound measurement of total plaque area (TPA) provides a method for quantifying carotid ...

Discovery of novel DGAT1 inhibitors by combination of machine learning methods, pharmacophore model and 3D-QSAR model.

DGAT1 plays a crucial controlling role in triglyceride biosynthetic pathways, which makes it an attr...

Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and Outcomes.

Peripheral artery disease is an atherosclerotic disorder which, when present, portends poor patient ...

Automated classification of coronary atherosclerotic plaque in optical frequency domain imaging based on deep learning.

BACKGROUND AND AIMS: We developed a deep learning (DL) model for automated atherosclerotic plaque ca...

Tinnitus Frequency is Higher in Patients with Chronic Heart Failure with Reduced Ejection Fraction and is Closely Related to NT-proBNP Level.

There is not enough information about tinnitus and related parameters in patients with heart failure...

A deep learning-based model for characterization of atherosclerotic plaque in coronary arteries using optical coherence tomography  images.

PURPOSE: Coronary artery events are mainly associated with atherosclerosis in adult population, whic...

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