Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five attributes of the training process. The results of the second experiment showed improvement in the performance of the KNN and the Multilayer Perceptron. The results of the second experiment showed a slight decrease in the performance of the Random Forest with 97.5 % accuracy.
Background: Cardiovascular disease (CVD) is an important complication of type 2 diabetes mellitus (T2DM). Oxidative stress plays a major role in the development of CVD. Saliva has a diagnostic properties aiding in the detection of systemic diseases. This study aimed to assess the association between salivary oxidative stress markers and the risk of vascular disease (VD) in T2DM patients. Materials and Methods: One hundred T2DM patients and fifty apparently healthy males were enrolled in this study. Saliva sample was collected for assessment of oxidative stress markers including: lipid peroxidation plasma thiobarbituric acid-reactive substances (TBARS), uric acid (UA) and total antioxidant capacity (TAC) levels. Arterial stiffness index (ASI
... Show MoreBackground: Improved glucose level control with insulin injections have allowed for the diabetic population to live longer and healthier lives. Unfortunately diabetes remains a worldwide epidemic disease with multiple health implications. Specifically, its effects upon fracture healing are compromised in diabetics with as high as 87% recovery delay relative to “healthy†counterparts. Current medical treatments for bone injuries have been largely focused on replacing the lost bone with allogenic or autogenous bone grafts, beta-tricalcium phosphate (β -TCP), a ceramic alloplast, has interconnected system of micropores, has been widely used as a biologically safe osteoconductive bone substitute. The aim of this study was histol
... Show MoreThe study aimed to evaluate Glucagon-Like Peptide-1 levels in Polycystic ovary syndrome (PCOS) infertile female with Diabetes Mellitus (DM) and compare the results with control group, also, to find the correlation for GLP-1 with Luteinizing hormone (LH), Follicle stimulating hormone (FSH) and LH/FSH ratio that may be used in prediction atherosclerosis in these patients. The study included nineteen women with age ranged (30-40) years and BMI ranged between (30-35) Kg/m 2. Subjects were divided into two groups: group (1) consist of (45) females as a healthy control and group (2) consist of (45) infertile females with PCOS and DM as complication. Fasting serum glucose was determined by using commercial kits (Biolabo SA-France); LH, FSH, prolac
... Show MoreDiabetes mellitus is a set of metabolic diseases, the most prevalent of which is chronic hyperglycemia. The culprits include insulin synthesis, insulin action, or both. Osteoporosis is a progressive systemic skeletal disorder defined by decreased bone mass and micro architectural degeneration of bone tissue, resulting in increased bone fragility and fracture risk, according to the World Health Organization (WHO). The degree of Nervosa damage determines how much a diabetic patient's body has been compromised. The current study's goal is an estimation: Age, BMI, FBS, HbA1C, D3, ALP, Ca, P, and Osteocalcin in Iraqi T2DM Women's patients with and without Osteoporosis. Three vitamins are required for Osteocalcin biosynthesis: vitamin K for Gla f
... Show MoreBackground: Many structural or functional abnormalities can impair the production of thyroid hormones and cause hypothyroidism.Objectives: to identify the main etiological causes of hypothyroidism among patients visiting Specialized Center for Diabetes and Endocrinology.Methods: This study was conducted in the Specialized Center for Diabetes and Endocrinology on 217 patients with proved hypothyroidism, from 2006 to 2008. Every patient was tested with thyroid function tests, Ultrasound examination, thyroid autoantibodies, fine needle aspiration, radiology of skull, isotopes scan, also checking adrenal and gonadal function. Results: Out of these 217 patients 120 patients have thyroiditis 33 patients had been undergone thyroidectomy. 39 pat
... Show More