Latest AI and machine learning research in diabetes for healthcare professionals.
BACKGROUND: Outcome prediction is important in the clinical decision-making process. Artificial neural networks (ANN) have been used to predict the risk of post-operative events, including survival, and are increasingly being used in complex medical decision making. We aimed to use ANN analysis to estimate predictive factors of in-hospital mortality (IHM) in patients with type 2 diabetes (T2DM) af...
BACKGROUND: The recent pandemic of obesity and the metabolic syndrome (MetS) has led to the realisation that new drug targets are needed to either reduce obesity or the subsequent pathophysiological consequences associated with excess weight gain. Certain nuclear hormone receptors (NRs) play a pivotal role in lipid and carbohydrate metabolism and have been highlighted as potential treatments for o...
Mixed cryoglobulinemic syndrome, which is a systemic vasculitis characterized by the immune complex deposition in small- and medium-sized arteries and...
As a chronic disease, diabetes mellitus has emerged as a worldwide epidemic. The aim of this study is to classify diabetes disease by developing an in...
The present study was aimed to evaluate the influence of olive, sesame and black seed oils on levels of some physiological parameters in male rats exp...
The aims of this study were: (1) to evaluate the effect of different insulin concentrations, alone or in combination with either a fixed FSH concentra...
AIMS: Evaluate efficacy and hypoglycaemia according to concomitant oral antidiabetes drug (OAD) in people with type 2 diabetes initiating insulin glar...
Thrombosis is a serious complication of many canine diseases and may be related to decreased fibrinolytic potential. Plasminogen activator inhibitor-1...
BACKGROUND: High molecular weight (HMW) adiponectin has antiatherogenic, antiinflammatory and antidiabetic properties and these effects have been link...
BACKGROUND: Effective glucose control in the intensive care unit (ICU) setting has the potential to decrease morbidity and mortality rates which shoul...
BACKGROUND: Osteoprotegerin (OPG) is a member of the tumor necrosis factor superfamily. Reduced OPG levels are related to obesity, insulin resistance,...
Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signa...
Postprandial increase in blood triglyceride levels is an independent risk factor for coronary artery disease, and dietary resistant starch (RS) is inc...
The diagnosis of metabolic syndrome (MetS) has a leading role in the early prevention of chronic disease, such as cardiovascular disease, type 2 diabe...
Statistical models to predict incident diabetes are often based on limited variables. Here we pursued two main goals: 1) investigate the relative perf...
Diabetes is a disease that has to be managed through appropriate lifestyle. Technology can help with this, particularly when it is designed so that it...
This paper presents Fuzzy-PID (FPID) control scheme for a blood glucose control of type 1 diabetic subjects. A new metaheuristic Cuckoo Search Algorit...
BACKGROUND AND OBJECTIVE: Diabetic retinopathy is one of the leading disabling chronic diseases and one of the leading causes of preventable blindness...
A 54-year-old man diagnosed with type 2 diabetes and hyperthyroidism was prescribed propylthiouracil (PTU) after the patient developed hepatic dysfunc...
OBJECTIVE: To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS...