AIMC Topic: Metabolic Syndrome

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Beneficial effects of Bifidobacterium lactis on lipid profile and cytokines in patients with metabolic syndrome: A randomized trial. Effects of probiotics on metabolic syndrome.

Nutrition (Burbank, Los Angeles County, Calif.) Dec 7, 2015
OBJECTIVE: Human studies have shown the beneficial effects of probiotic microorganisms on the parameters of metabolic syndrome (MetS) and other cardiovascular risks, but to our knowledge the effect of Bifidobacterium lactis has not yet been reported....
Humans Young Adult Adolescent Bifidobacterium Adult Metabolic Syndrome Cytokines Male Lipids Female Middle Aged Probiotics
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A model based on artificial intelligence for the prediction, prevention and patient-centred approach for non-communicable diseases related to metabolic syndrome.

European journal of public health Aug 1, 2025
Metabolic syndrome (MetS) is related to non-communicable diseases (NCDs) such as type 2 diabetes (T2D), metabolic-associated steatotic liver disease (MASLD), atherogenic dyslipidaemia (ATD), and chronic kidney disease (CKD). The absence of reliable t...
Male Middle Aged Risk Assessment Metabolic Syndrome Machine Learning Female Aged Adult Humans Patient-Centered Care Artificial Intelligence Noncommunicable Diseases
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Continual learning across population cohorts with distribution shift: insights from multi-cohort metabolic syndrome identification.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2025
OBJECTIVE: This study aims to tackle the critical challenge of adapting deep learning (DL) models for deployment in real-world healthcare settings, specifically focusing on catastrophic forgetting due to distribution shifts between hospital and non-h...
ROC Curve Nutrition Surveys Metabolic Syndrome Datasets as Topic Humans Deep Learning
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Integrating Artificial Intelligence in the Diagnosis and Management of Metabolic Syndrome: A Comprehensive Review.

Diabetes/metabolism research and reviews May 1, 2025
BACKGROUND: Metabolic syndrome (MetS) is a progressive chronic pathophysiological state characterised by abdominal obesity, hypertension, hyperglycaemia, and dyslipidaemia. It is recognised as one of the major clinical syndromes affecting human healt...
Artificial Intelligence Machine Learning Humans Prognosis Metabolic Syndrome Diabetes Mellitus, Type 2 Disease Management
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Predicting metabolic syndrome: Machine learning techniques for improved preventive medicine.

Health informatics journal Jan 1, 2025
Metabolic syndrome (MetS) has a significant impact on health. MetS is the umbrella term for a group of interdependent metabolic threats that contribute to the emergence of diseases that can lead to death. This study was designed to better predict th...
Prospective Studies Female Risk Factors Aged Humans Machine Learning Metabolic Syndrome Data Mining Adult Preventive Medicine Male Middle Aged
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Machine Learning-Assisted Analysis of Sublingual Microcirculatory Dysfunction for Early Cardiovascular Risk Evaluation and Cardiovascular-Kidney-Metabolic Syndrome Stage in Patients With Type 2 Diabetes Mellitus.

Diabetes/metabolism research and reviews Sep 1, 2024
AIMS: To examine whether sublingual microcirculation can be used as an effective and noninvasive method for assessing cardiovascular, kidney, and metabolic risks in patients with type 2 diabetes mellitus (T2DM).
Follow-Up Studies Metabolic Syndrome Heart Disease Risk Factors Carotid Intima-Media Thickness Cardiovascular Diseases Middle Aged Risk Assessment Diabetes Mellitus, Type 2 Microcirculation Mouth Floor Humans Machine Learning Prognosis Female Risk Factors Aged Cross-Sectional Studies Male
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An interpretable predictive deep learning platform for pediatric metabolic diseases.

Journal of the American Medical Informatics Association : JAMIA May 20, 2024
OBJECTIVES: Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the de...
Humans Metabolic Syndrome Electronic Health Records Area Under Curve Female Metabolic Diseases ROC Curve Male Deep Learning Prediabetic State Adolescent Diabetes Mellitus, Type 2 Child, Preschool Pediatric Obesity Child
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A nine-hub-gene signature of metabolic syndrome identified using machine learning algorithms and integrated bioinformatics.

Bioengineered Dec 1, 2021
Early risk assessments and interventions for metabolic syndrome (MetS) are limited because of a lack of effective biomarkers. In the present study, several candidate genes were selected as a blood-based transcriptomic signature for MetS. We collected...
Humans Machine Learning Algorithms Protein Interaction Maps Biomarkers Computational Biology Female Databases, Genetic Male Metabolic Syndrome Transcriptome
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Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

Metabolic syndrome and related disorders Nov 1, 2019
We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH), a stage of nonalcoholic fatty liver disease, (NAFLD) in which the inflammation of hepatocytes can lead to increased cardiovascular risk, liver fibr...
Liver Cirrhosis Hypertension Metabolic Syndrome Decision Making Non-alcoholic Fatty Liver Disease Humans Disease Progression Prevalence Cross-Sectional Studies Severity of Illness Index Machine Learning Female Male Diabetes Mellitus, Type 2 Algorithms Aged Middle Aged Prognosis Adult Retrospective Studies Sensitivity and Specificity
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Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2019
In 2005, global cardiovascular diseases caused 30% of deaths in Europe, which is 46% of total deaths for all death groups. Today, according to the International Adult Diabetes Federation, 20% to 25% of the adult population in the world has Metabolic ...
Fuzzy Logic Metabolic Syndrome Turkey Cardiovascular Diseases Humans Risk Assessment Female Decision Support Systems, Clinical Male
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