Dyslipidemia

Artificial neural networks in tandem with molecular descriptors as predictive tools for continuous liposome manufacturing.

The current study utilized an artificial neural network (ANN) to generate computational models to ac...

Atherosclerotic Burden and Remodeling Patterns of the Popliteal Artery as Detected in the Magnetic Resonance Imaging Osteoarthritis Initiative Data Set.

Background An artificial intelligence vessel segmentation tool, Fully Automated and Robust Analysis ...

Is Machine Learning-derived Low-Density Lipoprotein Cholesterol estimation more reliable than standard closed form equations? Insights from a laboratory database by comparison with a direct homogeneous assay.

BACKGROUND: There is no consensus on the best method to estimate Low Density Lipoprotein-Cholesterol...

Prediction of premature all-cause mortality in patients receiving peritoneal dialysis using modified artificial neural networks.

Premature all-cause mortality is high in patients receiving peritoneal dialysis (PD). The accurate a...

Kernel machine SNP set analysis finds the association of BUD13, ZPR1, and APOA5 variants with metabolic syndrome in Tehran Cardio-metabolic Genetics Study.

Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The ...

Drug repurposing for hyperlipidemia associated disorders: An integrative network biology and machine learning approach.

Hyperlipidemia causes diseases like cardiovascular disease, cancer, Type II Diabetes and Alzheimer's...

Regression plane concept for analysing continuous cellular processes with machine learning.

Biological processes are inherently continuous, and the chance of phenotypic discovery is significan...

Prediction of brain age from routine T2-weighted spin-echo brain magnetic resonance images with a deep convolutional neural network.

Our study investigated the feasibility and clinical relevance of brain age prediction using axial T2...

Pre-existing and machine learning-based models for cardiovascular risk prediction.

Predicting the risk of cardiovascular disease is the key to primary prevention. Machine learning has...

Enzymatic preparation of phytosterol esters with fatty acids from high-oleic sunflower seed oil using response surface methodology.

Phytosterol esters are functional compounds that can effectively reduce plasma cholesterol concentra...

Using CNN and HHT to Predict Blood Pressure Level Based on Photoplethysmography and Its Derivatives.

According to the WTO, there were 1.13 billion hypertension patients worldwide in 2015. The WTO encou...

Virtual Transcriptomics: Noninvasive Phenotyping of Atherosclerosis by Decoding Plaque Biology From Computed Tomography Angiography Imaging.

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Therapeutic Potentials of Selected Antihypertensive Agents and Their Fixed-Dose Combinations Against Trastuzumab-Mediated Cardiotoxicity.

Trastuzumab () is useful in the clinical management of HER2-positive metastatic breast, gastric, and...

Automated segmentation of the individual branches of the carotid arteries in contrast-enhanced MR angiography using DeepMedic.

BACKGROUND: Non-invasive imaging is of interest for tracking the progression of atherosclerosis in t...

Assessment of Thoracic Pain Using Machine Learning: A Case Study from Baja California, Mexico.

Thoracic pain is a shared symptom among gastrointestinal diseases, muscle pain, emotional disorders,...

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits.

Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes,...

Automated Histological Segmentation on Micro Computed Tomography Images of Atherosclerotic Arteries.

Association Between Coffee Intake and Incident Heart Failure Risk: A Machine Learning Analysis of the FHS, the ARIC Study, and the CHS.

BACKGROUND: Coronary heart disease, heart failure (HF), and stroke are complex diseases with multipl...

Automatic Lumen Border Detection in IVUS Images Using Deep Learning Model and Handcrafted Features.

In the clinical analysis of Intravascular ultrasound (IVUS) images, the lumen size is an important i...

Ultrasound-based internal carotid artery plaque characterization using deep learning paradigm on a supercomputer: a cardiovascular disease/stroke risk assessment system.

Visual or manual characterization and classification of atherosclerotic plaque lesions are tedious, ...

Towards a new model and classification of mood disorders based on risk resilience, neuro-affective toxicity, staging, and phenome features using the nomothetic network psychiatry approach.

Current diagnoses of mood disorders are not cross validated. The aim of the current paper is to expl...