<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>
Background: Several studies suggested that skeletal system is adversely affected by diabetes and is associated with increased risk of osteoporosis and fragility fractures
Objectives: The study was a case-control study that designed to assess the level of bone turnover markers (BTMs) among patients with type 2 diabetes mellitus (T2DM) and to investigate the effect of body weight and diabetic control on the level of bone turnover
Type of the study: Cross- sectional study.
Methods: The present study included 100 postmenopausal women with type 2 diabetes mellitus. Sixty-six non-diabetic postmenopausal women were enrolled as a control. Fasting b
... Show MoreBackground: Chronic hyperglycemia causes diabetic nephropathy(DN), which is a typical microvascular complication of type 2 diabetes mellitus. The pathogenesis of DN is not fully understanding. The inflammation may possess a significant role in the progression of DN in diabetic patients. Method: The study accomplished at teaching laboratories of medical city, Baghdad, Iraq. It was included 50uncontrolled diabetic type 2 patients with nephropathy, age range (40-78) years and 42 controlled diabetics type 2 without nephropathy, age range (35 - 52) years as a control group. The participants divided in to two groups according to HbA1c measurement which is described as follows: < 7.5% of HbA1c describes controlled diabetes, and > 9% of HbA1c
... Show MorePeople with diabetes can develop different foot problems. In the blood stream glucose reacts with hemoglobin to make a glycosylated hemoglobin molecule called hemoglobin A1c or HbA1c, the more glucose in the blood the more hemoglobin A1c will be present in the blood. The HbAlc test is currently one of the best ways to check diabetes to be under control. The aim of study is to compare between the blood investigations which includes the fasting blood sugar and HbAlC (glycosylated hemoglobin), and to evaluate the benefit of HbAlc (measurement for diabetic patients with foot ulcer, to be a good indicator for controlling blood glucose). Sixty patients with type2 diabetes mellitus from the outpatient clinic of Baghdad Teachin
... Show MoreObjective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio
Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m
... Show MoreThis study investigated the structural behavior of a beam–slab member fabricated using a steel C-Purlins beam carrying a profile steel sheet slab covered by a dry board sheet filled with recycled aggregate concrete, called a CBPDS member. This concept was developed to reduce the cost and self-weight of the composite beam–slab system; it replaces the hot-rolled steel I-beam with a steel C-Purlins section, which is easier to fabricate and weighs less. For this purpose, six full-scale CBPDS specimens were tested under four-point static bending. This study investigated the effect of using double C-Purlins beams face-to-face as connected or separated sections and the effect of using concrete material that contains different recycled
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreThe importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T
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