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Diabetes Prediction Using Machine Learning
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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.

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Publication Date
Sun Mar 18 2018
Journal Name
International Journal Of Pharmaceutical Quality Assurance
The Role of Soluble L-Selectin with Polymorphism in Iraqi Arabs Patients with Diabetes Mellitus Type 2
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Diabetes mellitus type 2 [DMT2] is a disturbance of metabolism and complex diseases influenced by environmental, genetic agents, and linked with inflammation, happens when the pancreas either does not use the insulin as it should or the body does not make enough insulin, lead to insulin resistance [IR] alongside with gradual loss of ß-cell secretory ability. The aim of this study was to investigate the role of soluble L-selectin (sL-selectin) in diabetes mellitus type 2 patients in Iraqi Arabs patient. Study includes seventy six Iraqi Arabs patients (male and female) having newly diagnosed type 2 diabetes mellitus (T2DM), with Fifty three Iraqi Arabs healthy subjects matched in age, sex and ethnic group. Patients and healthy subjec

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Publication Date
Thu Jan 01 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The prevalence of Candida spp. in the saliva of controlled and uncontrolled diabetes mellitus type II patients
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Background: Diabetes mellitus type 2 has been known for many years as the most common endocrine metabolic disorder that affect the oral cavity and cause many oral diseases including candidiasis. In this study, the incidence of Candida spp. in the saliva of controlled and uncontrolled diabetic patients were determined and compared with non diabetic group. Material and method: The sample consists of 200 subjects: 100 diabetic patients [57 (28.5%) uncontrolled diabetes, 43 (21.5%) controlled diabetes] and 100 (50%) non diabetic groups. Saliva samples was obtained from the subjects and cultured on selective media using appropriate microbiological method to observe the presence of Candida spp. Results: The results revealed a significant associat

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Publication Date
Thu May 04 2023
Journal Name
Biomedicine
Relationship between cathepsin K and total oxidative state in diabetes mellitus female patients with osteoporosis in Iraq
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Introduction and Aim: Diabetes mellitus patients almost always struggle with a metabolic condition known as chronic hyperglycemia. According to the World Health Organization, osteoporosis is a progressive systemic skeletal disorder that is characterized by decreasing bone mass and microstructural breakdown of bone tissue that increases susceptibility to fracture and increased risk of breaking a bone. Here, we aimed to compare the levels of CatK and total oxidative state in patients with diabetes and osteoporosis among the female Iraqi population and study the possible relationship between them.   Materials and Methods: This study included 40 females with diabetes (Group G1), 40 with diabetes and osteoporosis (Group G2) and 40 norma

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Publication Date
Tue Jan 01 2019
Journal Name
Current Research In Microbiology And Biotechnology
Detection of Anti-rubella virus, Cytomegalovirus and Chlamydia pneumonia antibodies in patients with type I diabetes mellitus
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Type-1 diabetes is defined as destruction of pancreatic beta cell, virus and bacteria are some environmental factor for this disease. The study included 25 patients with type-1 diabetes mellitus aged between 8 – 25 years from Baghdad hospital and 20 healthy persons as control group. Anti-rubella IgG and IgM, anti-Chlamydia pneumonia IgG and IgM were measured by ELISA technique while anti-CMV antibody were measured by immunofluorescence technique. The aim of current study was to know the trigger factor for type-1 diabetes. There were significant differences (P<0.05) between studied groups according to parameters and the results lead to suggest that Chlamydia pneumonia, CMV and rubella virus may trigger type-1 diabetes mellitus in Iraqi pat

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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
Study ABO/Rh system with Endothelial Inflammatory Factors in Iraqi Arab Female with Diabetes Mellitus Type II
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Diabetes mellitus type II is a disorder of metabolism and complex diseases affected by genetic environmental factors and associated with inflammation. The symptoms of type II diabetes develop gradually, which are associated with increased blood concentration of marker of the endothelial inflammatory factors. The expression of adhesion molecules, including E-selectin, intracellular adhesion molecule-1(ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) on the surface of vascular endothelial cells to help leukocyte stick to other surrounding tissues. Many researchers have made attempts to determine the significance of particular ABO phenotype for the susceptibility to diseases. Many reports show a strong association with the ABO blood grou

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Publication Date
Wed May 31 2023
Journal Name
International Journal Of Sustainable Development And Planning
Prediction of Formal Transformations in City Structure (Kufa as a Model) Based on the Cellular Automation Model and Markov Chains
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The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from

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Publication Date
Tue Dec 06 2022
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Blended Learning in Nursing Education at the Middle Region in Iraq
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Abstract

Objective(s): To evaluate blended learning in nursing education at the Middle Region in Iraq.

Methodology: A descriptive study, using evaluation approach, is conducted to evaluate blended learning in nursing education in Middle Region in Iraq from September 26th, 2021 to March 22nd, 2022. The study is carried out at two Colleges of Nursing at the University of Baghdad and University of Tikrit in Iraq. A convenient, non-probability, sample of (60) undergraduate nursing students is selected. The sample is comprised of (30) student from each college of nursing, Self-report questionnaire is constructed from the literature, for e

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Cognitive Beliefs and Their Relationship to Self-Organized Learning Strategies at the Preparatory Stage
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The study aims to identify the level of cognitive beliefs, as well as to identify the level of self-organized learning strategies among intermediate school students. The study also aims to identify the differences in the level of self-organized learning strategies among intermediate school students in term of gender, branch (scientific, literary). In order to achieve the research objectives, the researcher designed a scale to measure the cognitive beliefs. As for the scale of self-organized learning strategies, the researcher adopted a scale of (Pintrich et al. 1991), which was translated by (Izzat Abdelhamid, 1999) , For self-organized learning strategies, the sample consisted of (400) students from the research population, whic

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Effect Of Technology Based Learning As A Supplement To Traditional Technology On Student's Achievement
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This paper describes a practical study on the impact of learning's partners, Bluetooth Broadcasting system, interactive board, Real – time response system, notepad, free internet access, computer based examination, and interaction classroom, etc, had on undergraduate student performance, achievement and involving with lectures. The goal of this study is to test the hypothesis that the use of such learning techniques, tools, and strategies to improve student learning especially among the poorest performing students. Also, it gives some kind of practical comparison between the traditional way and interactive way of learning in terms of lectures time, number of tests, types of tests, student's scores, and student's involving with lectures

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