Latest AI and machine learning research in dyslipidemia for healthcare professionals.
Self-collection of biospecimens at-home, without specialized equipment or training, are increasingly being adopted in clinical practice due to convenience and patient preferences. However, sample instability during shipment means that remote access to common blood tests remains challenging. We hypothesized that the inaccuracy and imprecision in test results that develop because of sample instabili...
BACKGROUND: Chronic psychosocial stress induces cumulative physiological dysregulation that accelerates biological aging and contributes to the development of cerebrovascular and neurocognitive disorders, including stroke and cognitive impairment. The Allostatic Load Index (ALI) is a composite measure reflecting multisystem physiological wear and tear resulting from chronic stress and has been ass...
BACKGROUND: Preterm birth (PTB) is a major cause of neonatal morbidity and mortality. Inflammation and metabolic disruption are involved in its pathol...
AIMS/HYPOTHESIS: Data-driven subtyping of type 2 diabetes has not been translated into clinical practice due to the lack of routine fasting glucose an...
BACKGROUND: Accurate risk stratification post-myocardial infarction (MI) remains challenging. This study aimed to develop interpretable machine learni...
BACKGROUND: Hepatitis E virus (HEV) infection remains a major cause of liver failure with high short-term mortality, yet predictive models incorporati...
Escalating global electronic waste (e-waste) generation contrasts with <20% formal recycling rates. Policy gaps and inadequate enforcement exacerbate ...
Pericoronary adipose tissue (PCAT) is increasingly recognised as a biosensor of vascular inflammation. The guideline-driven widespread adoption of cor...
BACKGROUND: Carotid vessel wall segmentation and determination of the lumen area are crucial for the diagnosis of atherosclerosis. U-Net-based deep le...
PURPOSE: Frailty is increasingly recognized as a predictor of poor surgical outcomes, yet its preoperative assessment in patients with non-small-cell ...
Even foundational models trained on large-scale datasets may learn to rely on non-relevant artifacts such as background color or color intensity, lead...
Cardiovascular diseases (CVD) are becoming a serious threat to human health. These are considered the leading causes of mortality. Abnormal lipid conc...
PURPOSE: To discover novel systemic associations that may lead to idiopathic epiretinal membrane (iERM) using interpretable machine learning models. D...
BACKGROUND: With the accelerating aging of the global population, muscle health issue occurs commonly as an age-related process in older people. The c...
AIM: APOE genotype may affect statin therapy response. We conducted a meta-analysis to update and quantify this association across various outcomes. M...
BACKGROUND: Cardiorenal-protective sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) lack se...
Mobile health (mHealth)-based disease management programs enable continuous monitoring of blood pressure (BP) and related health behaviors. Feature en...
Insulin resistance is suggested to be a risk factor for cancer; however, large-scale epidemiological evidence linking insulin resistance to cancer rem...
Widely used in millions of atherosclerosis treatments, conventional metal stents, although pervasive, only provide mechanical support to narrowed arte...
Allostatic load scores (ALSs) quantify the cumulative physiological burden of sustained stress across neuro-endocrine, metabolic, cardiovascular and i...