Dyslipidemia

Long-term prognostic value of the CT-derived fractional flow reserve combined with atherosclerotic burden in patients with non-obstructive coronary artery disease.

OBJECTIVES: The long-term prognostic significance of the coronary computed tomography angiography (CCTA)-derived fractional flow reserve (CT-FFR) for non-obstructive coronary artery disease (CAD) is uncertain. We aimed to investigate the additional prognostic value of CT-FFR beyond CCTA-defined atherosclerotic burden for long-term outcomes.

Chatbot for the Return of Positive Genetic Screening Results for Hereditary Cancer Syndromes: Prompt Engineering Project.

The increasing demand for population-wide genomic screening and the limited availability of genetic counseling resources have created a pressing need for innovative service delivery models. Chatbots powered by large language models (LLMs) have shown potential in genomic services, particularly in pretest counseling, but their application in returning positive population-wide genomic screening resul...

Identification of lipid metabolism-associated biomarkers in lupus nephritis by SVM model and therapeutic potential of Alisol B 23-acetate.

Systemic lupus erythematosus (SLE), a multifaceted autoimmune disorder, has lupus nephritis (LN) as one of its grave complications and is strongly ass...

Identification of key proteins and pathways in myocardial infarction using machine learning approaches.

Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for im...

A hybrid GAN-based deep learning framework for thermogram-based breast cancer detection.

Breast cancer remains one of the most prevalent and life-threatening diseases among women worldwide, necessitating early and accurate detection method...

Out-of-distribution reject option method for dataset shift problem in early disease onset prediction.

Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, its predictive accuracy for u...

Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy,...

A novel outreach approach for identification of familial hypercholesterolemia: Interview-based formative evaluation to improve healthcare access and quality.

BACKGROUND: Familial hypercholesterolemia (FH) is a genetic condition which elevates cholesterol levels and increases risk of premature cardiac events...

The Application of Machine Learning in Warfarin Dose Precision for Diabetic Patients Treated with Statins: A Comparative Study.

PURPOSE: To evaluate the impact of statin therapy on warfarin dose requirements in diabetic patients and to assess the performance of various machine ...

Assessing the stress hyperglycemia ratio in hyperlipidemia patients to predict all-cause mortality: A retrospective cohort study.

BACKGROUND: The Stress Hyperglycemia Ratio (SHR) reflects stress-related hyperglycemia and is linked to poor outcomes in various diseases. This study ...

Evaluating the impact of metabolic indicators and scores on cardiovascular events using machine learning.

Cardiovascular diseases such as coronary artery disease, myocardial infarction, and heart failure impact millions of people annually globally and are ...

Mild to moderate COPD, vitamin D deficiency, and longitudinal bone loss: the Multi-ethnic Study of Atherosclerosis.

OBJECTIVE: Despite the established association between chronic obstructive pulmonary disease (COPD) severity and risk of osteoporosis, even after acco...

Macrophage histone lactylation in atherosclerosis progression: mechanisms, predictive models, and therapeutic potential of Ruan Jian Qing Mai formula.

AIMS: This study investigates the role of macrophage histone lactylation-a protein modification-in atherosclerosis progression, particularly in periph...

Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.

Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative...

Aging at the Crossroads of Organ Interactions: Implications for the Heart.

Aging processes underlie common chronic cardiometabolic diseases such as heart failure and diabetes. Cross-organ/tissue interactions can accelerate ag...

Blunted Niacin Skin Flushing Response in Schizophrenia: A Meta-analysis.

BACKGROUND AND HYPOTHESIS: The multifactorial pathogenesis of schizophrenia (SZ) hinders the diagnosis and treatment of this disorder. Niacin skin flu...

Identification of shared mechanisms between Alzheimer's disease and atherosclerosis by integrated bioinformatics analysis.

Alzheimer's disease (AD) and atherosclerosis (AS) are two interacting diseases mostly affecting aged adults. AD is characterized by the deposition of ...

Machine learning algorithms to predict the risk of hyperlipidemia in people living with HIV after starting HAART for 6 months.

OBJECTIVE: The purpose of this study was to use machine learning models to predict the risk of hyperlipidemia in people living with HIV (PLWHs) for 6 ...

Discovery of novel potential 11β-HSD1 inhibitors through combining deep learning, molecular modeling, and bio-evaluation.

11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) has been shown to play an important role in the treatment of impaired glucose tolerance, insulin re...

Association between atherogenicity indices and prediabetes: a 5-year retrospective cohort study in a general Chinese physical examination population.

BACKGROUND AND OBJECTIVE: Atherogenicity indices have emerged as promising markers for cardiometabolic disorders, yet their relationship with prediabe...