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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
Sat Feb 01 2020
Journal Name
International Journal Of Computer Science And Mobile Computing
Hierarchical Fixed Prediction of Mixed based for Medical Image Compression.
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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
Thu Dec 23 2010
Journal Name
Arabian Journal Of Geosciences
Climatic prediction of the terrestrial and coastal areas of Iraq
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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Creep-Fatigue Interaction Damage for Polyamide 6,6 Composites
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    This paper aims to study the damage generated due to creep-fatigue interaction behaviors in solid polyamide 6,6 and its composites that include 1%wt of carbon nanotubes or 30% wt short carbon fiber prepared by an injection technique. The investigation also includes studying the influence of applied temperatures higher than the glass transition temperatures on mechanical properties. The obtained results showed that the addition of reinforcement materials increased all the mechanical properties, while the increase in test temperature reduced all mechanical properties, especially for polyamide 6,6. The creep-fatigue interaction resistance also improved due to the addition of reinforcement materials by inc

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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
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Prediction of Biodegradability Possibility for Sewage of the Dairy Industry
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he dairy industry is one of the industrial activities classified within the food industries in all phases of the dairy industry, which leads to an increase in the amount of wastewater discharged from this industry. The study was conducted in the Abu Ghraib dairy factory, classified as one of the central factories in Iraq, located in the west of Baghdad governorate, with a design capacity of 22,815 tons of dairy products. The characteristics of the liquid waste generated from the factory were determined for the following parameters biological oxygen demand (BOD5), Chemical oxygen demand (COD), total suspended solids (TSS), pH, nitrate, phosphate, chloride, and sulfate with an average value of (1079, 1945, 323, 9.2, 24, 2

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Publication Date
Wed Mar 01 2017
Journal Name
Neural Computing And Applications
The potential of nonparametric model in foundation bearing capacity prediction
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Publication Date
Mon Jun 04 2018
Journal Name
Baghdad Science Journal
Disturbance of Arginase Activity and Nitric Oxide Levels in Iraqi Type 2 Diabetes Mellitus
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This study is an attempt to find whether arginine metabolism dysregulation by arginase activity is related to hyperglycemia, followed by changes in nitric oxide (NO) generation in type 2 diabetic patients. This study includes 42 control subjects (Group I), and 92 Iraqi patients with type 2 diabetes mellitus (T2DM). The patient group was subdivided into two groups: Group II (54) with T2DM only and Group III (38) with T2DM and dyslipidemia (who were treating with atorvastatin along with diabetes treatment). The samples were obtained to measure arginase activity and NO levels. Serum arginase activity increased significantly in patients(groupII and groupIII) compared to control group. While serum NO level was significantly lower in diabetic pa

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Comparison Study between Adipsin Levels in Sera of Iraqi Patients with Diabetes and Neuropathy
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The current study was designed to compare some of the vital markers in the sera of diabetic and neuropathy patients via estimating Adipsin, Fasting blood Glucose(FBG), Glycated(HbA1c) hemoglobin, Homeostasis Model Assessment Index (Homa IR ), Cholesterol, High density lipoprotein (HDL), Triglycerides (T.G), Low-density, and lipoprotein (LDL), Very Low Density Lipoprotein (VLDL), in sera of Iraqi patients with diabetes and neuropathy. A total  of ninety  subjects  were divided into three groups: group I (30 diabetic with neuropathy males) and group II (30 diabetic males without neuropathy), and 30 healthy sujects were employed as control group. The results showed a significant decline in Adipsin levels (p>0.05) in neuropathy, T2DM g

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Publication Date
Thu Nov 01 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Association between infant Feeding Practices and Insulin – Dependent Diabetes Mellitus (IDDM)
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Abstract The percent study aimed to determination the association between infant feeding practices and Insulin-Dependent Diabetes Mellitus (IDDM). The study was conducted at (he National Center of Diabetes in Baghdad City the Capital of Iraq throughout the period of January 2001 to January 2002. The sample was comprised of (200) mother of Insulin-Dependent Diabetes Mellitus (IDDM) of children under age of 12 years old. Data was collected through the use of a questionnaire that constructed by researcher and which were developed for the purpose of the present study. Reliability of the instruments was dete

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