AIMC Topic: Metabolic Syndrome
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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.
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,...
The circadian syndrome is a better predictor for psoriasis than the metabolic syndrome via an explainable machine learning method - the NHANES survey during 2005-2006 and 2009-2014.
Frontiers in endocrinology
Jun 26, 2024
OBJECTIVE: To explore the association between circadian syndrome (CircS) and Metabolic Syndrome (MetS) with psoriasis. Compare the performance of MetS and CircS in predicting psoriasis.
Machine Learning Identification of Nutrient Intake Variations across Age Groups in Metabolic Syndrome and Healthy Populations.
Nutrients
May 28, 2024
This study undertakes a comprehensive examination of the intricate link between diet nutrition, age, and metabolic syndrome (MetS), utilizing advanced artificial intelligence methodologies. Data from the National Health and Nutrition Examination Surv...
Risk prediction model of metabolic syndrome in perimenopausal women based on machine learning.
International journal of medical informatics
May 9, 2024
INTRODUCTION: Metabolic syndrome (MetS) is considered to be an important parameter of cardio-metabolic health and contributing to the development of atherosclerosis, type 2 diabetes. The incidence of MetS significantly increases in postmenopausal wom...
Deep learning imaging phenotype can classify metabolic syndrome and is predictive of cardiometabolic disorders.
Journal of translational medicine
May 8, 2024
BACKGROUND: Cardiometabolic disorders pose significant health risks globally. Metabolic syndrome, characterized by a cluster of potentially reversible metabolic abnormalities, is a known risk factor for these disorders. Early detection and interventi...
Metabolic phenotyping with computed tomography deep learning for metabolic syndrome, osteoporosis and sarcopenia predicts mortality in adults.
Journal of cachexia, sarcopenia and muscle
Apr 22, 2024
BACKGROUND: Computed tomography (CT) body compositions reflect age-related metabolic derangements. We aimed to develop a multi-outcome deep learning model using CT multi-level body composition parameters to detect metabolic syndrome (MS), osteoporosi...
The relationship between heavy metals and metabolic syndrome using machine learning.
Frontiers in public health
Apr 15, 2024
BACKGROUND: Exposure to high levels of heavy metals has been widely recognized as an important risk factor for metabolic syndrome (MetS). The main purpose of this study is to assess the associations between the level of heavy metal exposure and Mets ...
Artificial intelligence facial recognition system for diagnosis of endocrine and metabolic syndromes based on a facial image database.
Diabetes & metabolic syndrome
Apr 3, 2024
AIM: To build a facial image database and to explore the diagnostic efficacy and influencing factors of the artificial intelligence-based facial recognition (AI-FR) system for multiple endocrine and metabolic syndromes.
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