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Evaluation of Ultrasonography in the Diagnosis of Acute Appendicitis with Histopathology as Gold Standard
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Background: Acute appendicitis is the most common surgical abdominal emergency with a life time prevalence of 1 to 7 individuals. Because the clinical diagnosis of acute appendicitis remains a challenge to surgeons, so different aids were introduced like different scoring systems, computer aided programs, ultrasonography, computerized tomography, Magnetic resonance imaging, Gastrointestinal tract contrast studies and laparoscopy to improve the diagnostic accuracy.

Objective: To evaluate ultrasound in the diagnosis of acute appendicitis in those patients clinically diagnosed with histopathology as gold standard.

Methods: A cross sectional study carried in Al-kindy Teaching Hospital through one year duration from 1st of may2015 to1st of May 2016. All included patients were subjected to ultrasonographic examination to assess the vermiform appendix with a graded compression technique. The Ultrasonography findings were recorded as positive and negative for acute appendicitis.

All the appendices removed from the study patients were sent for histopathological study. Statistical analysis done using (SPSS) version 21, Chi-sequare test used for categorical variables and t-test was used to compare between two means. Level of significance (P value) set at ≤ 0.05.

Results: A total of 215 patients with suspected appendicitis, males 112 (52.09%) and females 103(47.9%) were included in present study. The validity results of ultrasound in comparison with histopathology findings were as following; accuracy 86.5%, sensitivity 86.5%, specificity 86.6%, positive predictive value 99.8% and negative predictive value 32.5%.

Conclusion: The ultrasonography has a good accuracy, sensitivity and specificity in diagnosing acute appendicitis.

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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Fingerprints Identification and Verification Based on Local Density Distribution with Rotation Compensation
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The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
peridos for transversal coincidence maps on compact manifolds with a given cohomology
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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Thermal Efficiency for Passive Solar Chimney with and Without Heat Storage material
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In this study, a different design of passive air Solar Chimney(SC)was tested by installing it in the south wall of insulated test room in Baghdad city. The SC was designed from vertical and inclined parts connected serially together, the vertical SC (first part) has a single pass and Thermal Energy Storage Box Collector (TESB (refined paraffin wax as Phase Change Material(PCM)-Copper Foam Matrix(CFM))), while the inclined SC was designed in single pass, double passes and double pass with TESB (semi refined paraffin wax with copper foam matrix) with selective working angle ((30o, 45o and 60o). A computational model was employed and solved by Finite Volume Method (FVM) to simulate the air i

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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Publication Date
Wed Mar 29 2023
Journal Name
Aip Conference Proceedings
(𝓹,𝔼)-convex sets and (𝓹,𝔼)-Convex functions with their properties
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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Educational And Psychological Researches
Effective dialogue and its relationship with some variables at Baghdad University Students
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     Increasing need for our youth to effective dialogue at the present time, due to the nature of the era in which live, as it abounded risk of intellectual and cultural invasion.Moreover, the need to ensure that the dialogue between the members of the community to confront the many issues of contemporary society in various fields, politically, socially and economically, culturally and religiouslyThe absence of effective dialogue, or the consequent rejection of many of the negative aspects of social and cultural Kaezzlh coup and inertia and ignore the mental capacity of some non-existent among others.The importance of effective dialogue in being the most important foundations of social life a

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Publication Date
Tue Jul 15 2008
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
riol] and its Complexes with Co", Ni 9, Cu º, and Znº.
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The reaction of 2, 4, 6-trihydroxyactophenonemonohydrate with hydrazine monohydrate was realized under reflux in methanol and a few drops of glacial acetic acid were added to give the (intermediate) 2-(1-hydrazono-ethyl)-benzene-1, 3, 5-triol, which reacted with salicylaldehyde in methanol to give a new type (NO) ligand [HL][(2-1-[(2-hydroxy-benzyliidene)-hydrazono]-ethyl) benzene-1, 3, 5-triol. The ligand was reacted with Mcl.(where M-Co, Ni, Cu, and Zn) under reflux in methanol with (l: 1) ratio to give complexes of the general formula [M (HL)]. All compounds have been characterized by spectroscopic methods I" H NMR, IR. UV-Vis, HPLC, atomic absorption] microanalysis along with conductivity measurement. From the above data the proposed mo

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Publication Date
Wed Sep 30 2020
Journal Name
Neuroquantology
Superconducting Compound Hg0.8Sb0.2Ba2Ca2Cu3O8+δ Compared with Hg0.8Sb0.2Ba2Ca1Cu2O6+δ to Evaluate Transition Temperature
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The high temperature superconductor’s compounds are one of the hot spot field of science, due to their applications in industries. Hg0.8Sb0.2Ba2Ca2Cu3O8+δ and Hg0.8Sb0.2Ba2Ca1Cu2O6+δ, were manufactured using a doable-step of solid state reaction method. The samples were sintered at 800 ° C. The transition temperatures Tc are found from electrically resistively by using four probe techniques. The resistivity become zero when the transition temperature Tc(offset) have 131 and 119 K, and the onset temperature Tc(onset) have 139 K for Hg0.8Sb0.2Ba2Ca2Cu3O8+δ and 132 K for Hg0.8Sb0.2Ba2Ca1Cu2O6+δ. Analysis of X-ray diffraction showed a tetragonal structure with lattice parameters changes for all samples.

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Wed Nov 12 2025
Journal Name
Journal Of Physical Education
Special Endurance And its Relationship With 10 Km Walking Achievement for Youth
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