AIMC Topic: Metabolic Syndrome
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The utility of an artificial intelligence model based on decision tree and evolution algorithm to evaluate steatotic liver disease in a primary care setting.
Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
Jun 16, 2025
Many ways of classifying steatotic liver disease (SLD) with metabolic conditions have been proposed. Thus, SLD-related variables were verified using a decision tree. We tested if the suggested components of the actual classification (metabolic dysfun...
Integrated muti-omics data and machine learning reveal CD151 as a key biomarker inducing chemoresistance in metabolic syndrome-related early-onset left-sided colorectal cancer.
Functional & integrative genomics
Jun 9, 2025
Emerging evidence has suggested a potential pathological association between early-onset left-sided colorectal cancer (EOLCC) and metabolic syndrome (MetS). However, the underlying genetic and molecular mechanisms remain insufficiently elucidated. Th...
Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China.
Journal of health, population, and nutrition
Jun 4, 2025
BACKGROUND: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pathophysiological interactions between the cardiovascular system, chronic kidney disease, and metabolic risk factors. In China, the prevalence of CKM i...
Effect of visceral fat on onset of metabolic syndrome.
Scientific reports
May 30, 2025
This study analysed the effects of visceral fat on metabolic syndrome (MetS) and developed an algorithm to predict its onset using health examination data from the Iwaki Health Promotion Project in Japan. The dataset included 213 cases of MetS onset ...
Identification of diagnostic genes for myocardial ischemia reperfusion injury associated with metabolic syndrome through the integration of bioinformatics analysis, molecular docking and experimental validation.
Frontiers in immunology
May 29, 2025
BACKGROUND: Metabolic dysregulation in metabolic syndrome (MetS) exacerbates myocardial ischemia-reperfusion injury (MIRI). This study aimed to identify diagnostic biomarkers and therapeutic candidates for MetS-associated MIRI.
Assessing the association of multi-environmental chemical exposures on metabolic syndrome: A machine learning approach.
Environment international
Apr 17, 2025
Metabolic syndrome (MetS) is a major global public health concern due to its rising prevalence and association with increased risks of cardiovascular disease and type 2 diabetes. Emerging evidence suggests that environmental chemical exposures may pl...
Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study.
Cardiovascular diabetology
Apr 16, 2025
BACKGROUND: The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting the increasing importance of the complex interplay between metabolic, renal, and cardiovascular diseases (CVD)....
Male
Cardiovascular Diseases
Middle Aged
Risk Assessment
Prognosis
Female
Risk Factors
Aged
Insulin Resistance
Longitudinal Studies
Metabolic Syndrome
Kidney Diseases
Predictive Value of Tests
China
Blood Glucose
Incidence
Time Factors
Humans
Machine Learning
Decision Support Techniques
Prospective Studies
Biomarkers
Development and validation of a machine learning model for predicting pediatric metabolic syndrome using anthropometric and bioelectrical impedance parameters.
International journal of obesity (2005)
Apr 1, 2025
OBJECTIVE: Metabolic syndrome (MS) is a risk factor for cardiovascular diseases, and its prevalence is increasing among children and adolescents. This study developed a machine learning model to predict MS using anthropometric and bioelectrical imped...
Gender Differences in Predicting Metabolic Syndrome Among Hospital Employees Using Machine Learning Models: A Population-Based Study.
The journal of nursing research : JNR
Apr 1, 2025
BACKGROUND: Metabolic syndrome (MetS) is a complex condition that captures several markers of dysregulation, including obesity, elevated blood glucose levels, dyslipidemia and hypertension. Using an approach to early prediction of MetS risk in hospit...
Deep-learning analysis of greenspace and metabolic syndrome: A street-view and remote-sensing approach.
Environmental research
Mar 7, 2025
Evidence linking greenspace exposure to metabolic syndrome (MetS) remains sparse and inconsistent. This exploratory study evaluate the relationship between green visibility index (GVI) and normalized difference vegetation index (NDVI) with MetS preva...
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