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Prenatal Markers of Foetal Complications

Prenatal markers are commonly used in practice to screen for some foetal abnormalities. They can be biochemical or ultrasonic markers in addition to the newly used cell free Deoxyribonucleic Acid (DNA) estimation. This review aimed to illustrate the applications of the prenatal screening, and the reliability of these tests in detecting the presence of abnormal chromosomes such as trisomy-21, trisomy-18, and trisomy-13 in addition to neural tube defects. Prenatal markers can also be used in the anticipation of some obstetrical complications depending on levels of these markers in the mother’s circulation. In the developed countries, prenatal screening tests are regularly used during antenatal care period. Neural tube defects, numerical and structural chromosomal abnormalities, in addition to some obstetrical problems are commonly screened for, by using prenatal tests. Maternal education about the importance of performing these tests should be done in order to improve the detection rate of foetal abnormalities and some pregnancy complications.

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fully Automated Magnetic Resonance Detection and Segmentation of Brain using Convolutional Neural Network

     The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks

Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

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Publication Date
Thu May 28 2020
Journal Name
Iraqi Journal Of Science
An Artificial Neural Network for Predicting Rate of Penetration in AL- Khasib Formation – Ahdeb Oil Field

The main objective of this study is to develop a rate of penetration (ROP) model for Khasib formation in Ahdab oil field and determine the drilling parameters controlling the prediction of ROP values by using artificial neural network (ANN).

     An Interactive Petrophysical software was used to convert the raw dataset of transit time (LAS Readings) from parts of meter-to-meter reading with depth. The IBM SPSS statistics software version 22 was used to create an interconnection between the drilling variables and the rate of penetration, detection of outliers of input parameters, and regression modeling. While a JMP Version 11 software from SAS Institute Inc. was used for artificial neural modeling.

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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
Effect Of Vêo® Premium and Vitamin C Supplementation on Lipid Profile Before and During Pregnancy in Some Local Iraqi Ewes During Heat Stress

The present study was designed to investigate the effects of VêO® premium and vitamin C (Vit. C) supplementation on lipid profile before and during pregnancy in local Iraqi ewes during heat stress. The study was conducted in a private field in Fallujah city, west Iraq, during the period from 6/8/2019 to 8/2/2020. Twenty local Iraqi ewes were divided randomly into four equal groups (5 for each group) The first group (T1) was given VêO® premium (4 g/ ewe/ day), the second group (T2) was given VêO® premium (2 g/ ewe/ day), and the third group (T3) was given Vit. C (40 mg/ ewe/ day), and the fourth group (T4) was left without treatment, as a control group. Aft

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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network

Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Thu Mar 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks

Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

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Publication Date
Fri May 01 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
Bone Cutter Circumcision in Neonates

Background: Bone cutter is widely used in the
Middle east area to cut the prepuce during circumcision.

Results :One hundred twenty one male neonates
were included in this study.The mean operative
time (MOT) was 6 minutes, mean time of
healing (MTH) was 5 days, 7 cases (5.9%)
developed early & late complications, 2 (1.7%)
had bleeding, 3 (2.5%) developed infection, 2
(1.7%) developed late complications in the form
of meatal stenosis.
Settings:Al-Yarmouk Teaching Hospital and a
private surgical clinic.
Aim of the study: To assess the safety of
circumcision using bone cutter.
Methods: Over 6 years period from Jan. 2000
till Dec. 2005, one hundred twenty one male
neonates were circumci

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Publication Date
Wed Jan 30 2013
Journal Name
Al-kindy College Medical Journal
Primary repair versus diversion in penetrating colon injuries

Back ground: In Iraq, after 2003 had more
accidents of the shell, bullet and stab abdominal
wounds, more over colon injuries.
Objective: The aim of this study is to evaluate
the most appropriate management of penetrating
colon injuries, comparing the primary repair with
the diversion.
Methods: Eighty patient series with shell, bullet
and stab colonic injuries during 4.5 years period
from June 2006-december 2010 at Al-Yarmouk
teaching hospital. The study compared the use of
primary repair versus diversion, analyzing
variables such as sex, age, severity of injury and
mortality rate.
Results: there were total 80 patients ,62 (77.5%)
male and 18(22.5%) female .male :female ratio
3.4:1. the most

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