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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
Wed Dec 01 2021
Journal Name
International Journal Bioautomation
Model for Prediction of the Weight and Height Measurements of Patients with Disabilities for Diagnosis and Therapy
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Background: Accurate measurement of a patient’s height and weight is an essential part of diagnosis and therapy, but there is some controversy as to how to calculate the height and weight of patients with disabilities. Objective: This study aims to use anthropometric measurements (arm span, length of leg, chest circumference, and waist circumference) to find a model (alternatives) that can allow the calculation of the height and the body weight of patients with disabilities. Additionally, a model for the prediction of weight and height measurements of patients with disabilities was established. Method: Four hander patients aged 20-80 years were enrolled in this study and divided into two groups, 210 (52.5%) male and 190 (47.5%) fe

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Publication Date
Sun Jun 01 2025
Journal Name
Irish Journal Of Medical Science (1971 -)
Enhanced diagnostic accuracy of type 1 diabetes mellitus through the combined use of serum β-catenin and HbA1c
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Publication Date
Tue May 17 2016
Journal Name
Iosr Journal Of Nursing A Nd Health Science (iosr-jnhs)
Comparative Study of Abnormal Renal Function Tests and Liverfunction Tests in Type1 and Type2 Diabetes Mellitus in Iraq
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This study was planned to evaluate the renal function tests and liver function tests and it carried out in Al-Yarmouk hospital,Baghdad –Iraqin patients withtype 1 and type 2 diabetes mellitus by measuring(uric acid,urea and creatinine) ,Aspartate aminotransferase (AST) and Alanine aminotransferase (ALT). Seventy five individuals of Iraqi adults (male) were divided into three groups, 25 patients with type1 diabetes mellitus ,25 patients with type 2 diabetes mellitus and 25 normal individuals were taken as control group. The mean value of uric acid, urea and creatinine was higher significantly in patients thanin control group (P< 0.05),while the correlation(p< 0.01) between age ,creatinine in type 1 and between age and (Urea, Uric acid ,cr

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Publication Date
Sun May 12 2013
Journal Name
International Journal Of Pharmacy And Pharmaceutical Sciences
PLEIOTROPIC EFFECTS OF ATORVASTATIN ON PRO-INFLAMMATORY CYTOKINES IN NEWLY DIAGNOSED IRAQI PATIENTS WITH TYPE 2 DIABETES MELLITUS
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Objective: Atorvastatin therapy is now recommended for reduction of cardiovascular risk in type 2 diabetic patients (T2DM), based on convincing evidence of reductions in mortality and vascular events in major clinical outcome trials. The aim is to evaluate the effects of atorvastatin on proinflammatory markers (TNF-α, IL-6), HbA1c andleptin in obese patients with type 2 diabetes. Methods: Sixty fivenewly diagnosed T2DM patients were randomly allocated into 2 groups; group I treated with metformin only; in group II atorvastatin was added with metformin. Twenty healthy subjects were enrolled as control group. While maintaining their usual eating habits, fasting blood samples were collected at baseline and after 12 weeks of treatment. Results

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Publication Date
Thu Oct 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A study of Hepcidin levels and other Biochemical parameters in woman with Osteoporosis with Type 2 Diabetes Mellitus
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Background: Diabetes mellitus (DM) could be regarded as a set of chronic metabolic disorders which have a common aspect of hyperglycemia. The resistance in the peripheral actions of insulin or impaired insulin secretion could be the reason  hepcidin which is a peptide hormone derived from liver, in systemic iron homeostasis is an essential regulator, and its lopsided production participates in the pathogenesis of iron disorders in spectrum. Osteoporosis often accompanies many diseases like ß-thalassemia, hemochromatosis, sickle liver diseases, cell disease and hemosiderosis featured by iron overload, evidences suggest that Iron overload and iron deficiency are suggested by evidences that they affect bone in a negative way, acting

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Publication Date
Tue Aug 30 2022
Journal Name
Research Journal Of Pharmacy And Technology
The Distribution of ABO blood groups among type 2 Diabetes mellitus patients with or without Chronic Microvascular Complications
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The ABO blood group system is highly polymorphic, with more than 20 distinct sub-groups; study findings are usually related to ABO phenotype, but rarely to the ABO genotype and animal models are unsatisfactory because their antigen glycosylation structure is different from humans. Both the ABO and Rh blood group systems have been associated with a number of diseases, but this is more likely related to the presence or absence of these tissue antigens throughout the body and not directly or primarily related to their presence on RBCs. A total of fifty-two 52 patients without complication of DMII, two hundred sixteen 216 patients with complication of DMII and seventy-one 71 person as healthy control were included in the study. The resu

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Association of Endothelin-I and A symmetric Dimethylarginine Levels with Insulin Resistance in Type-2 Diabetes Mellitus Patients
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Endothelin-I (ET-I) is one of the potent vasoconstrictors secreted from endothelial cells when needed. Many studies revealed the elevation of serum ET-I with human diabetes and microangiopathies. Since insulin resistance is a case of mixed diabetic and pre-diabetic cases, many risk factors beyond obesity and inflammation are proposed. The current study aims to demonstrate the association between serum ET-I and asymmetric dimethylarginine (ADMA) and insulin resistance in type 2 diabetes mellitus (T2DM). Sera of 73 subjects were enrolled currently (control= 35 subjects, and 38 with T2DM for more than 7 years), aged (40-60) years old, with distinct body mass index (BMI) ≤ 25 for control volunteers and (BMI) ≥ 25 for obesity and diabetes

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Scientific Development For Studies And Research
The Role of E-Learning in teaching the Arabic language to non- native speakers
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After the information revolution that occurred in the Western world, and the developments in all fields, especially in the field of education and e-learning, from an integrated system based on the effective employment of information and communication technology in the teaching and learning processes through an environment rich in computer and Internet applications, the community and the learner were able to access information sources and learning at any time and place, in a way that achieves mutual interaction between the elements of the system and the surrounding environment. After the occurrence of the phenomenon of Covid 19, it led to a major interruption in all educational systems that had never happened before, and the disrupt

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Tue Dec 25 2018
Journal Name
Summaries Of Working Papers, Research And Experiments
E-learning at the College of Mass Communication, subject: public relations campaigns as a model
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