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Analyzing the behavior of different classification algorithms in diabetes prediction
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<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>

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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 Sep 30 2025
Journal Name
International Journal On Engineering Applications (irea)
Prediction of Trips Attraction to the Central Business District of Al Nasiriyah City Utilizing an Artificial Neural Network Model
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Estimation of trip attraction and analyzing its main influencing factors are powerful for offering different classifications for business districts and presenting recommendations for improving attractiveness in long term. This is beneficial for designing transportation facilities and infrastructures. The paper presents the prediction of trip attraction using an artificial intelligence technology due to the profits that the technology can possess in shortening time, lowering expenses and saving effort. The new model has utilized six input parameters that have not been considered previously within the area of Nasiriyah city including; age and educational level of the passengers, mode of transport that the passengers use, purpose of the trip,

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Publication Date
Wed Nov 06 2024
Journal Name
2024 17th International Conference On Development In Esystem Engineering (dese)
Improving Cardiovascular Prediction Performance Using Machine Learning Based Feature Selection
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Mon Mar 13 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Computer Assisted Immunohistochemical Score Prediction Via Simplified Image Acquisition Technique
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Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Veterinary Sciences
Evaluation of antidiabetic activity of zinc oxide and chromium oxide nanoparticles alone or in combination on the pancreas of alloxan-induced diabetes mellitus in male albino mice (Mus musculus)
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Zinc is an essential element for the body; it is involved in many enzymes and has a role in many physiological processes; glucose metabolism stands ahead of them. Also, chromium has been used recently as a food supplement in regime systems, So it's essential to evaluate the effects of these two elements in a diabetic state and evaluate their antidiabetic ability. Seventy male adult mice were used and grouped into seven groups. Group 1: received no treatment. Group 2 received 10mg/kg body weight daily orally of ZnONPs for a month. Group 3 received 1mg/kg body weight for a month daily oral of CrO3NPs. Group 4: received a single dose of 150mg/kg body weight of alloxan. Group 5 received a single alloxan dose of 150 mg/kg and daily oral 10 mg/kg

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Publication Date
Mon Mar 30 2026
Journal Name
Iraqi Journal Of Science
Analyzing Materials and Determining their Physical Properties Using Spectral Sensing Technology from Satellite Images: Methodology and Applications
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The spectral remote sensor technology was used to study the Kurdistan region of Iraq to determine the characteristics of surface minerals and by analyzing satellite images across multiple spectral ranges, distinctive spectral signatures were specified for several metals such as zinc (ZN), Lead (PB), and Parium (BA), as well as the use of thermal infrared to detect free abnormalities and the results were verified through field measurements and admonitory, where the selection accuracy was 85% according to the absolute error (MAPE) and 0.045 for RMSé and the results showed that spectral signatures for metals were distributed in nearby and remote IR ranges, helping to determine mineral sediments such as zinc and lead in carbonate rocks

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Studying the Effect of Different Separating Medium on the Roughness of the tissue surface of Acrylic Denture Base (In Vitro Study)
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Objective: In order to evaluate the effect of different typed of Separating Medium on the roughness of the fitted
tissue surface of acrylic denture base.
Methodology: Chosen three types of separating medium (Group A Tin foil), (Group B Detery Isolant),(Group C
Cold Mould Seal),used 30 samples of hot cure acrylic resin ,10 samples for each group, after complete curing of
these samples , Profilometer device was used to measure the surface roughness of each sample in all groups.
Results: Using One Way ANOVA Test and LSD test, the results were highly significant in differences among all
groups. Although (Group A) showing lest roughness, (Group B) showing a satisfactory result of roughness, While
(Group C) Showing the hig

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