AIMC Topic: Metabolic Syndrome
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Unveiling the ageing-related genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning.
Artificial cells, nanomedicine, and biotechnology
Mar 1, 2025
Ageing significantly contributes to osteoarthritis (OA) and metabolic syndrome (MetS) pathogenesis, yet the underlying mechanisms remain unknown. This study aimed to identify ageing-related biomarkers in OA patients with MetS. OA and MetS datasets an...
Machine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007-2016.
Scientific reports
Jan 25, 2025
Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but...
Nonlinear relationship between serum Klotho and chronic kidney disease in US adults with metabolic syndrome.
Frontiers in endocrinology
Dec 24, 2024
BACKGROUND: Current evidence regarding the effects of serum Klotho among patients with metabolic syndrome (MetS) is scarce. This study explored the relationship between serum Klotho levels and the odds of chronic kidney disease (CKD) in middle-aged a...
Machine learning algorithms that predict the risk of prostate cancer based on metabolic syndrome and sociodemographic characteristics: a prospective cohort study.
BMC public health
Dec 20, 2024
BACKGROUND: Given the rapid increase in the prevalence of prostate cancer (PCa), identifying its risk factors and developing suitable risk prediction models has important implications for public health. We used machine learning (ML) approach to scree...
Gene-diet interactions in carbonated sugar-sweetened beverage consumption and metabolic syndrome risk: A machine learning analysis in a large hospital-based cohort.
Clinical nutrition ESPEN
Oct 11, 2024
BACKGROUND AND AIM: Carbonated sugar-sweetened beverages (CSSB) intake has been increasingly linked to metabolic diseases. To investigate the association between CSSB intake and metabolic syndrome (MetS) risk, and the interaction between genetic pred...
Metabolic syndrome predictive modelling in Bangladesh applying machine learning approach.
PloS one
Sep 5, 2024
Metabolic syndrome (MetS) is a cluster of interconnected metabolic risk factors, including abdominal obesity, high blood pressure, and elevated fasting blood glucose levels, that result in an increased risk of heart disease and stroke. In this resear...
Prediction of metabolic syndrome using machine learning approaches based on genetic and nutritional factors: a 14-year prospective-based cohort study.
BMC medical genomics
Sep 4, 2024
INTRODUCTION: Metabolic syndrome is a chronic disease associated with multiple comorbidities. Over the last few years, machine learning techniques have been used to predict metabolic syndrome. However, studies incorporating demographic, clinical, lab...
A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.
Scientific reports
Aug 1, 2024
Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced high-density lipoprotein cholesterol, and impaired glucose tolerance. It...
Identification of diagnostic genes and drug prediction in metabolic syndrome-associated rheumatoid arthritis by integrated bioinformatics analysis, machine learning, and molecular docking.
Frontiers in immunology
Jul 29, 2024
BACKGROUND: Interactions between the immune and metabolic systems may play a crucial role in the pathogenesis of metabolic syndrome-associated rheumatoid arthritis (MetS-RA). The purpose of this study was to discover candidate biomarkers for the diag...
Artificial intelligence chatbots for the nutrition management of diabetes and the metabolic syndrome.
European journal of clinical nutrition
Jul 26, 2024
BACKGROUND: Recently, there has been a growing interest in exploring AI-driven chatbots, such as ChatGPT, as a resource for disease management and education.
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