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Diabetes Prediction Using Machine Learning

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 Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images

Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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Publication Date
Thu Oct 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Pressure Control of Electro-Hydraulic Servovalve and Transmission Line Effect

The effected of the long transmission line (TL) between the actuator and the hydraulic control valve sometimes essentials. The study is concerned with modeling the TL which carries the oil from the electro-hydraulic servovalve to the actuator. The pressure value inside the TL has been controlled by the electro-hydraulic servovalve as a voltage supplied to the servovalve amplifier. The flow rate through the TL has been simulated by using the lumped π element electrical analogy method for laminar flow. The control voltage supplied to servovalve can be achieved by the direct using of the voltage function generator or indirect C++ program connected to the DAP-view program built in the DAP-card data acqu

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Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Estimating the Survival Function for the Patients Suffer from the Lung Cancer Disease

          In this paper, the survival function has been estimated for the patients with lung cancer using different parametric estimation methods depending on sample for completing real data which explain the period of survival for patients who were ill with the lung cancer based on the diagnosis of disease or the entire of patients in a hospital for a time of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the estimation of the survival function for the lung cancer by using pre-test singles stage shrinkage estimator method was the best   . <

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
New Versions of Liu-type Estimator in Weighted and non-weighted Mixed Regression Model

This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Thu Apr 13 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimate Complete the Survival Function for Real Data of Lung Cancer Patients

 In this paper, we estimate the survival function for the patients of lung cancer using different nonparametric estimation methods depending on sample from complete real data which describe the duration of survivor for patients who suffer from the lung cancer based on diagnosis of disease or the enter of patients in a hospital for period of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the survival function for the lung cancer by using shrinkage method is the best

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
The investment Decision Making According to the Preliminary Feasibility Study for the 100-Bed Teaching Hospital - Service Sector in Diwaniya Governorate (Case Study)

     The research aims to prepare a preliminary feasibility study that shows the importance of preliminary feasibility study in investment decision making, carrying out of the local demand of service provided in accordance with international standards and statement of investment opportunities available to the private sector in several investment methods. In order to reach the objectives of the study was adopted as a method of partial analysis at the level of economic unity through the study demand, supply, costs, economic and social profitability.

      The health sector in Iraq is one of the service sectors facing today a continuous deficiency

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of The College Of Languages (jcl)
Structural-Semantic and Stylistic Characteristics of the New Idioms in Russian Language: Структурно-семантическая и стилистическая характеристика новых фразеологизмов русского языка

This study is dedicated to one of the most difficult topics in Russian - this is the science of idioms. A feature of the Russian speech application in recent decades has been the effective change in the lexical composition of the Russian language. This article illustrates the semantic, grammatical and stylistic structural characteristics of the linguistic units that appeared in Russian at the end of the 20th century - the beginning of the twenty-first century. This work defines these terms : terminology, linguistic unity, and terms that are used as synonyms. In this research , we will adhere to the conciliatory view of the problem and include not only the terminology in the language units, but also the terminological compositions, saying

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Publication Date
Sun Oct 01 2006
Journal Name
Journal Of The Faculty Of Medicine Baghdad
The Impact Of Severity Of Ischaemia In Acute Coronary Syndrome On The Extent Of Coronary Artery Disease At Angiography The Role Of Past Ischaemia

Background: Clinical classification of patients with acute coronary syndrome is essential step in identifying severe cases before referring them, fairly quickly, for the ultimate investigation of coronary angiography .Hence it is important to find out the extent at which the severity of the disease, based on clinical classification, agrees with its severity at angiography and to see whether traditional Risk factors or pas ischaemia played a role.
Patients and Methods : The angiographer data of 178 consecutive pts with Acute Coronary Syndrome (ACS) were retrospectively analyzed. The pts consisted of 114 with Unstable Angina (UA)  and 64 pts with Non-ST-Segment Elevation Myocardial Infarction (NSTEMI). Pati

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