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A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve Bayesian classifier (NBC) have been enhanced as compared to the dataset before applying the proposed method. Moreover, the results indicated that issa was performed better than the statistical imputation techniques such as deleting the samples with missing values, replacing the missing values with zeros, mean, or random values.

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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical & Cellular Archives
TOXOPLASMOSIS, DIABETES AND SOME IMMUNE FACTORS THAT EFFECT ON THE BURDEN OF PATIENTS’ IMMUNITY
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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Prevalence of Depression among Mothers of Children with Type 1 Diabetes Mellitus attending two Diabetes Centers
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Publication Date
Wed Dec 12 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Parents' Knowledge about Type I Diabetes Mellitus at Diabetes and Endocrine Treatment Centers in Baghdad City
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Objectives: The current study aims to evaluate parents' knowledge towards diabetes mellitus (type I); to identify the association between parents' knowledge and their demographic characteristics; and to identify the association between parents' knowledge and demographic characteristics of their children. Methodology: Descriptive study carried out during the period from January to April 2015 on purposive sample of 100 parents with their children with diabetes mellitus who attending diabetes and endocrine treatment center. An evaluation tool is constructed by the researcher based on previous literature regarding

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Publication Date
Thu Mar 09 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
IFN-γ T/A +874 Gene Polymorphism in Type 1 Diabetes Mellitus of Iraqi Children
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This study included 50 blood samples collected from children with mean age 8-12 years. Thirty five blood samples were collected from children with Type 1 Diabetes Mellitus (T1D) with mean age 9.4±0.34 years, and 15 blood samples collected from healthy children as a control sample with mean age 10.9±0.38 years. Immunogenetic study was done on collected blood samples. Concentrations of IFN-γ were estimated from T1D patient and control samples by using Elisa instrument. The concentration of this interferon was 1.575 pg/ml in T1D patient sample in comparison with 0.921 pg/ml in control sample. Significant differences of this interferon concentration were found between T1D patient and control samples when Mann-Whitney U test was used

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Publication Date
Sun Apr 03 2011
Journal Name
لمؤتمر العلمي الرابع لكلية التربية/ جامعة سامراء
A comparison between alanine aminopeptidase (AAP) activity in type 2 diabetes and diabetic cardiac patients.
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Publication Date
Sat Jan 01 2022
Journal Name
Intelligent Automation & Soft Computing
A Novel Classification Method with Cubic Spline Interpolation
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Publication Date
Wed Mar 01 2017
Journal Name
جامعة كرميان
The effect of a training program for chemistry teachers based on the strategy of both sides of the brain together on the thinking patterns of their students
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The classification of fetus gender based on fuzzy C-mean using a hybrid filter
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This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Effect Of Technology Based Learning As A Supplement To Traditional Technology On Student's Achievement
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This paper describes a practical study on the impact of learning's partners, Bluetooth Broadcasting system, interactive board, Real – time response system, notepad, free internet access, computer based examination, and interaction classroom, etc, had on undergraduate student performance, achievement and involving with lectures. The goal of this study is to test the hypothesis that the use of such learning techniques, tools, and strategies to improve student learning especially among the poorest performing students. Also, it gives some kind of practical comparison between the traditional way and interactive way of learning in terms of lectures time, number of tests, types of tests, student's scores, and student's involving with lectures

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Classification of Fetus Gender Based on Fuzzy C-Mean Using a Hybrid Filter
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Abstract<p>This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT), (median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Lap</p> ... Show More
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