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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 Dec 01 2013
Journal Name
Baghdad Science Journal
Assessment of Inflammasome Activity in Type 2 Diabetes Mellitus and Simple Obesity: Comparative Study
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Inflammasome is a multiprotein oligomer complex which is the precursor procaspase-1 and is a component of the innate immune system so that this study aimed to determine the serum levels of interleukin-1? and 18 in patients with T2D and simple obesity in an attempt to clarify the role of inflammasome in these disorders.Twenty five known cases of T2D, twenty four patients with simple obesity and twenty healthy subjects were randomly recruited from AL-Kindy Teaching Hospital in Baghdad to enroll in this study. All the data about the demographic characteristics and anthropometric measurements were determined in all patients, also the C-reactive protein and serum interleukin (IL)-1? and IL-18 levels were obtained from each patient. The results s

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Publication Date
Wed Jan 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
The extent of UMOD gene polymorphism and its level in type 2 diabetes patients
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Publication Date
Mon Jul 23 2018
Journal Name
Journal Of Clinical Nursing
Factors influencing nurses’ knowledge acquisition of diabetes care and its management: A qualitative study
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Aim

To identify and explore the factors nurses perceive as influencing their knowledge acquisition in relation to diabetes care and its management in Saudi Arabia.

Background

Diabetes continues to pose major healthcare challenges despite advances in diabetes management. Nurses have a crucial role in diabetes care, but diabetes knowledge deficits deter effective collaboration with other healthcare providers in educating patients about diabetes self‐management.

Design

An exploratory descriptive qualitative design.

Method
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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Detection of Type 2 Diabetes Mellitus in Serum from Women with Polycystic Ovarian Syndrome
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Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorder. To determine the metabolic disorders in women with PCOS, (25) women with PCOS ages (15 - 47) years have been investigated and compared with (20) healthy individuals. All the studied groups were carried out to measure fasting blood sugar, (anti-GAD Ab, anti ?-islet cell Ab by IFAT) and measured insulin level by ELISA. There was significant elevation in the concentration of fasting blood sugar than in control groups (p ? 0.05) and there was negative results for anti-GAD Ab and anti ?-islet cell Ab by IFAT test for serum of women with PCOS, while there was significant differences in the insulin level for women with PCOS compared with control groups (p ? 0.05), these

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Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Quality of Life of Parents of Children with Type I Diabetes Mellitus, Baghdad 2017
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Background: Diabetes is defined by the World Health Organization as a metabolic disorder characterized by chronic hyperglycemia with disturbances of carbohydrate, fat and protein metabolism resulting from defects in insulin secretion, insulin action, or both. Families are co-regulating systems in which the stresses and strains of one family member affect the well-being of another member of the family. Caregivers of children with chronic illness report experiencing more parental stress than parents of healthy children.

Objective: A descriptive cross-sectional study had been conducted in four centers of endocrine diseases in Baghdad city and data was collected by using self-administered questionnaire regarding qua

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Publication Date
Tue Jan 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Nephrotic range proteinuria; does it predict lung involvement in patients with type 2 diabetes
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Publication Date
Tue Jan 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Nephrotic range proteinuria; does it predict lung involvement in patients with type 2 diabetes
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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Sat Aug 01 2026
Journal Name
Journal Of Physical Education
The Effect of Inclusion Style Using Electronic Device On Learning Front and Side Movement in Squash For Beginners Aged 13 – 15 Years Old
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