AIMC Topic: Hyperlipidemias

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Towards real-time non-invasive detection of hyperlipidemia through finger pulse image analysis using deep learning.

Biomedical physics & engineering express
Hyperlipidemia detection involves invasive, time-consuming procedures requiring clinical laboratories and blood samples. Often asymptomatic in its early stages, hyperlipidemia significantly increases the risk of cardiovascular diseases. The objective...

Unveiling the diagnostic and causal role of hyperlipidemia- and lipophagy-associated genes PLAUR, IVNS1ABP, and QKI in acute myocardial infarction.

International journal of cardiology
BACKGROUND: Hyperlipidemia (HLP) exacerbates myocardial cell injury by impairing lipophagy, a crucial lipid metabolic process, thereby increasing the risk of acute myocardial infarction (AMI). This study aims to identify biomarkers associated with HL...

Nuciferine activates intestinal TAS2R46 to attenuate metabolic disorders and hyperlipidemia via hepatic VLDL regulation.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: Dysregulated blood lipid metabolism, a primary driver of hyperlipidemia, is closely associated with excessive very low-density lipoprotein (VLDL) synthesis and secretion. Nuciferine, a bioactive compound isolated from lotus leaves, demons...

The Use of an Artificial Intelligence Platform OpenEvidence to Augment Clinical Decision-Making for Primary Care Physicians.

Journal of primary care & community health
BACKGROUND: Artificial intelligence (AI) platforms can potentially enhance clinical decision-making (CDM) in primary care settings. OpenEvidence (OE), an AI tool, draws from trusted sources to generate evidence-based medicine (EBM) recommendations to...

Integration of machine learning and experimental validation reveals new lipid-lowering drug candidates.

Acta pharmacologica Sinica
Hyperlipidemia, a major risk factor for cardiovascular diseases, is associated with limitations in clinical lipid-lowering medications. Drug repurposing strategies expedite the research process and mitigate development costs, offering an innovative a...

Artificial intelligence in therapeutic management of hyperlipidemic ocular pathology.

Experimental eye research
Hyperlipidemia has many ocular manifestations, the most prevalent being retinal vascular occlusion. Hyperlipidemic lesions and occlusions to the vessels supplying the retina result in permanent blindness, necessitating prompt detection and treatment....

A deep learning-based system for assessment of serum quality using sample images.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Serum quality is an important factor in the pre-analytical phase of laboratory analysis. Visual inspection of serum quality (including recognition of hemolysis, icterus, and lipemia) is widely used in clinical laboratories but is time-con...

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

Computational biology and chemistry
Hyperlipidemia causes diseases like cardiovascular disease, cancer, Type II Diabetes and Alzheimer's disease. Drugs that specifically target HL associated diseases are required for treatment. 34 KEGG pathways targeted by lipid lowering drugs were use...

Comparing a novel machine learning method to the Friedewald formula and Martin-Hopkins equation for low-density lipoprotein estimation.

PloS one
BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) is a target for cardiovascular prevention. Contemporary equations for LDL-C estimation have limited accuracy in certain scenarios (high triglycerides [TG], very low LDL-C).

Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture.

World neurosurgery
BACKGROUND: Machine learning (ML) has been increasingly used in medicine and neurosurgery. We sought to determine whether ML models can distinguish ruptured from unruptured aneurysms and identify features associated with rupture.