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INNOVATE GESTATIONAL AGE ESTIMATION MODEL FOR IRAQI FETUSES BASED ON ULTRASOUND IMAGES MEASUREMENTS
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Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify for Iraqi population and leading to some error in GA estimation results, so the objective of this study is to innovate GA estimation model for Iraqi people. This study was performed in the department of Obstetrics and Gynecology in Al- Yarmouk Teaching Hospital and AL- Alawiya Teaching Hospital in Baghdad, Iraq, during 2019 on 200 pregnant women of singleton and normal pregnancies, fetal GA (20-40) weeks (W). The obtained dataset (fetal biometry), were utilized to create GA estimation model in Iraq using IBM SPSS Version 23 software package (IBM^® Software). The statistical analysis of proposed GA model showed, the correlation (R) of model is 0.987 it is very high value and this is a good result to obtain the best regression model. as well as the Std error of Estimation was 0.61095 this is very small value and indicate the best result. The significant of model P=0.000 That means the model, as a whole, is a significant fit to the data (because P < 0.05).

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economic And Administrative Science
On Shrinkage Estimation for Generalized Exponential Distribution
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression based on Non-Linear Polynomial Prediction Model
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
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Akaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR).

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Publication Date
Sat Jun 25 2022
Journal Name
International Journal Of Drug Delivery Technology
Expression of Urotensin II of Human Placental Tissues and in Serum in Gestational Diabetic Mellitus in Iraqi Woman
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The placenta is an organ between the mother and fetus necessary for fetal growth and development. Gestational diabetes mellitus (DM) is the most frequent metabolic condition detected during pregnancy. It is characterized as hyperglycemia of various severity with onset or first detection during pregnancy that does not clearly describe any form of preexisting diabetes. Urotensin II (UII), a pluripotent vasoactive peptide, is important in developing insulin resistance. This study aimed to determine the level of Urotensin II(UII) in placenta and in the serum of diabetic and nondiabetic women. Methods The blood and placenta tissue collected from 50 ladies had been enrolled in this research ( 25 females with uncomplicated), (25 women with gestati

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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Ecology
Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Drug Delivery Technology
Histopathological Changes in Placentas of Gestational Hypertension Women
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Publication Date
Sun Dec 01 2024
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimation of a Circular Regression Model on Peak Systolic Blood Pressure Data
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Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro

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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of Baghdad College Of Dentistry
Radiological age estimation using third molars mineralization in a sample attending orthodontic clinics (A retrospective study)
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Background: The evaluation of the chronological age is a practical method in crime investigation field that assists in identifying individuals to treat them as underage or adult. This study aimed to assess the stages of third molars mineralization in relation to chronological age of Iraqi individuals, determine the gender differences and arches (maxillary/mandibular) differences.

Materials and Methods: A total of 300 orthopantomograms of orthodontic patients were collected according to specific criteria and evaluated visually. The developmental stages of maxillary and mandibular third molars were determined according to Demirjian method. T

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Publication Date
Tue Mar 01 2022
Journal Name
Results In Engineering
Predictive model for stress at ultimate in internally unbonded steel tendons based on genetic expression programming
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