AIMC Topic: Dyslipidemias
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Out-of-distribution reject option method for dataset shift problem in early disease onset prediction.
Scientific reports
Jun 2, 2025
Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, its predictive accuracy for use is often hindered by dataset shift, which refers to discrepancies in data distribution between th...
Association between atherogenicity indices and prediabetes: a 5-year retrospective cohort study in a general Chinese physical examination population.
Cardiovascular diabetology
May 21, 2025
BACKGROUND AND OBJECTIVE: Atherogenicity indices have emerged as promising markers for cardiometabolic disorders, yet their relationship with prediabetes risk remains unclear. This study aimed to comprehensively evaluate the associations between six ...
Potential Modulatory Roles of Gut Microbiota and Metabolites in the Associations of Macronutrient-to-Physical Activity Ratios With Dyslipidemia.
Journal of the American Heart Association
May 15, 2025
BACKGROUND: Lifestyle factors toward diet and physical activity (PA) may directly influence the pathophysiology of dyslipidemia. However, the associations of the specific macronutrient-to-PA ratio with dyslipidemia, and the underlying mechanisms rega...
Early prediction of postpartum dyslipidemia in gestational diabetes using machine learning models.
Scientific reports
Mar 7, 2025
This study addresses a gap in research on predictive models for postpartum dyslipidemia in women with gestational diabetes mellitus (GDM). The goal was to develop a machine learning-based model to predict postpartum dyslipidemia using early pregnancy...
Predicting dyslipidemia in Chinese elderly adults using dietary behaviours and machine learning algorithms.
Public health
Dec 19, 2024
OBJECTIVES: We aimed to predict dyslipidemia risk in elderly Chinese adults using machine learning and dietary analysis for public health.
Estimating the prevalence of select non-communicable diseases in Saudi Arabia using a population-based sample: econometric analysis with natural language processing.
Annals of Saudi medicine
Oct 3, 2024
BACKGROUND: Non-communicable diseases (NCDs) are a major public health challenge globally, including in Saudi Arabia. However, measuring the true extent of NCD prevalence has been hampered by a paucity of nationally representative epidemiological stu...
Predicting dyslipidemia incidence: unleashing machine learning algorithms on Lifestyle Promotion Project data.
BMC public health
Jul 3, 2024
BACKGROUND: Dyslipidemia, characterized by variations in plasma lipid profiles, poses a global health threat linked to millions of deaths annually.
Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening.
Cell reports. Medicine
Jun 28, 2024
Infrared spectroscopy is a powerful technique for probing the molecular profiles of complex biofluids, offering a promising avenue for high-throughput in vitro diagnostics. While several studies showcased its potential in detecting health conditions,...
Prevalence of non-communicable chronic diseases in rural India amongst peri- and post-menopausal women: Can artificial intelligence help in early identification?
Maturitas
May 16, 2024
AIMS: To identify peri- and post-menopausal women at risk of non-communicable diseases in rural India and to assess their prevalence amongst these groups via the use of artificial intelligence.
Estimation of low-density lipoprotein cholesterol levels using machine learning.
International journal of cardiology
Jan 20, 2022
BACKGROUND: Low-density lipoprotein-cholesterol (LDL-C) is used as a threshold and target for treating dyslipidemia. Although the Friedewald equation is widely used to estimate LDL-C, it has been known to be inaccurate in the case of high triglycerid...
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