AIMC Topic: Insulin Resistance
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Artificial intelligence model with deep learning in nonalcoholic fatty liver disease diagnosis: genetic based artificial neural networks.
Nucleosides, nucleotides & nucleic acids
Nov 30, 2022
Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease in the world. The NAFLD spectrum includes simple steatosis, steatohepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Genetic, nutritio...
Dietary administration of D-chiro-inositol attenuates sex-specific metabolic imbalances in the 5xFAD mouse model of Alzheimer's disease.
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Apr 26, 2022
Increasing evidence shows that hypothalamic dysfunction, insulin resistance, and weight loss precede and progress along with the cognitive decline in sporadic Alzheimer's Disease (AD) with sex differences. This study aimed to determine the effect of ...
Polycystic ovary syndrome: clinical and laboratory variables related to new phenotypes using machine-learning models.
Journal of endocrinological investigation
Sep 15, 2021
PURPOSE: Polycystic Ovary Syndrome (PCOS) is the most frequent endocrinopathy in women of reproductive age. Machine learning (ML) is the area of artificial intelligence with a focus on predictive computing algorithms. We aimed to define the most rele...
Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes.
Canadian journal of diabetes
Sep 6, 2021
OBJECTIVES: Circulating insulin concentrations mediate vascular-inflammatory and prothrombotic factors. However, it is unknown whether interindividual differences in circulating insulin levels are associated with different inflammatory and prothrombo...
The Use of Machine Learning Techniques to Determine the Predictive Value of Inflammatory Biomarkers in the Development of Type 2 Diabetes Mellitus.
Metabolic syndrome and related disorders
Feb 16, 2021
Certain inflammatory biomarkers, such as interleukin-6, interleukin-1, C-reactive protein (CRP), and fibrinogen, are prototypical acute-phase parameters that can also be predictors of cardiovascular disease. However, this inflammatory response can a...
Trace element, immune and opioid biomarkers of unstable angina, increased atherogenicity and insulin resistance: Results of machine learning.
Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS)
Dec 4, 2020
BACKGROUND: Aberrations in endothelial cells, immune and oxidative pathways are associated with atherosclerosis (ATS) and unstable angina (UA). The role of trace elements, minerals, and the endogenous opioid system (EOS) in UA are less well establish...
[Leptin sexual dimorphism, insulin resistance, and body composition in normal weight prepubescent].
Revista chilena de pediatria
Oct 21, 2020
INTRODUCTION: The prepubertal stage is a critical period of body fat development, in which leptin and insulin re sistance has been associated, however, there are few studies in normal-weight prepubescents. Ob jective: To assess the relationship betwe...
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.
PloS one
Dec 11, 2019
Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifications and drug intervention can prevent diabetes, therefore, an early identification of high risk individuals is important to design targeted preven...
Different spexin level in obese vs normal weight children and its relationship with obesity related risk factors.
Nutrition, metabolism, and cardiovascular diseases : NMCD
Nov 23, 2019
BACKGROUND AND AIMS: Spexin (SPX) is a novel peptide recently discovered as an important regulatory adipokine in obesity and related metabolic diseases. The aim of the current study was to determine the potential role of Circulating levels of SPX in ...
TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records.
Computers in biology and medicine
Jul 17, 2019
BACKGROUND: Insulin resistance is an early-stage deterioration of Type 2 diabetes. Identification and quantification of insulin resistance requires specific blood tests; however, the triglyceride-glucose (TyG) index can provide a surrogate assessment...
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