To identify risk factors, neural network analysis is used to create disease prediction models, including diabetes. The goals of this study were diabetes factors and determine their relative contribution using artificial intelligence as a mode prediction. current investigation was led by breaking down the dataset, shown below. We chose dataset from Kaggle. India. It has 763 female members, 497 w...

More than 50,000 active-duty U.S. Air Force (USAF) service members, retirees, and family members with diabetes receive care at more than 50 military treatment facilities (MTFs) throughout the continental United States.1 Although many of these patients are referred to civilian network diabetes specialists because of a scarcity of military endocrinologists, most are managed by USAF primary care p...

Models based on an artificial neural network (the multilayer perceptron) and binary logistic regression were compared in their ability to differentiate between disease-free subjects and those with impaired glucose tolerance or diabetes mellitus diagnosed by fasting plasma glucose. Demographic, anthropometric and clinical data were collected from 7222 participants aged 30-88 years in the Tehran ...

BACKGROUND The hypothesis was tested that the systemic immune milieu in recent-onset type 1 diabetes is associated with residual beta cell function and other metabolic patient characteristics. METHODS AND FINDINGS All patients (n = 89, 40% female) of the Diabetes and Atorvastatin (DIATOR) Trial were analyzed at recruitment, i.e. prior to receiving the study medication. Inclusion criteria were...

Diabetes is one of the most prevalent diseases in the world. Type 1 diabetes is characterized by the failure of synthesizing and secreting of insulin because of destroyed pancreatic β-cells. Type 2 diabetes, on the other hand, is described by the decreased synthesis and secretion of insulin because of the defect in pancreatic β-cells as well as by the failure of responding to insulin because of...

PURPOSE To establish, using adaptive optics scanning laser ophthalmoscopy (AOSLO), that the retinal parafoveal capillary network is altered before the onset of diabetic retinopathy in adult patients with type 2 diabetes. METHODS AOSLO videos were acquired in the parafoveal region of one eye from control subjects and from patients with type 2 diabetes and no retinopathy. Detailed images of the...

1Human Neurotransmitters Laboratory, Baker IDI Heart & Diabetes Institute, Melbourne, VIC 8008, Australia 2Nucleus Network Ltd., Baker IDI Heart & Diabetes Institute, Melbourne, VIC 8008, Australia 3Endocrinology and Metabolic Disease, VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, Los Angeles, CA 90073, USA 4Faculty of Medicine, Nursing and Health Science...

Type 2 diabetes mellitus is a complex disorder associated with multiple genetic, epigenetic, developmental, and environmental factors. Animal models of type 2 diabetes differ based on diet, drug treatment, and gene knockouts, and yet all display the clinical hallmarks of hyperglycemia and insulin resistance in peripheral tissue. The recent advances in gene-expression microarray technologies pre...

Huge amount of medical data is available today. In order to predict the disease we need a reliable method to diagnose the disease. In this paper we introduce a technique known as FFBAT-ANN prediction algorithm which is categorized as Feature reduction and Diabetes disease classification and such a process is carried out using LPP algorithm and FFBATartificial neural network classifier respectiv...