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bsj-527
Determination of Serum CA125 and evaluate its efficiency as screening tool For Early Detection of Ovarian Tumors
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Epithelial ovarian cancer is the leading cause of cancer deaths in women. To date, an effective screening tool for ovarian cancer has not been identified Several clinical and biological factors including serum cancer antigen 125 (CA- 125) have been assessed for prognostic and predictive relevance CA-125 is an epithelial marker derived from coelomic epithelium. It is elevated in 90% of advanced ovarian cancers and in 50% of early ovarian cancers while 20% of ovarian cancers have low or no expression of CA- 125 CA-125 concentrations were measured by Mini Vidas test (VIDAS CA125 II / BIOMERIEUX / France). The median CA-125 levels were significantly higher in the sera of ovarian cancer patients than in those with benign tumors and in healthy controls. However in correlation with stages the results showed that Patients with stage II have highly significant differences in level of serum CA125 compare with stage I in and stage III.CA125 showed low sensitivity to detect stage I carcinoma of the ovary which limits its value as an initial screening tool therefore combining of CA125 with other markers might enable improved early detection of ovarian cancer as compared with use of this marker alone.

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Publication Date
Tue Oct 04 2022
Journal Name
Ieee Access
Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

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Publication Date
Wed Apr 28 2021
Journal Name
2021 1st Babylon International Conference On Information Technology And Science (bicits)
Enhanced Twitter Community Detection using Node Content and Attributes
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Credit Card Fraud Detection Challenges and Solutions: A Review
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     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c

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Publication Date
Wed Jan 01 2020
Journal Name
Plant Archives
Evaluation of the efficiency of some mineralogical and organic materials to remove some heavy metals from contaminated soil
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Publication Date
Wed Sep 12 2012
Journal Name
Al- Taqani
EFFECT OF POTASSIUM FERTILIZERS APPLICATION ON GROWTH, YIELD AND WATER USE EFFICIENCY OF POTATO UNDER REGULATED IRRIGATION TREATMENTS
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Publication Date
Tue Jun 01 2021
Journal Name
Annals Of The Romanian Society For Cell Biology
Comparative Study of Serum Angiopoietin like Protein-8 and Hyaluronic Acid in Iraqi Hemodialysis Patients with and without T2DM
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The current work was designed to investigate serum angiopoietin like protein-8 and hyaluronic acid among Iraqi hemodialysis patients with and without type 2 diabetes mellitus, and to find relationship between them, as well as if these patients are at risk of kidney fibrosis. Subjects & Methods: in this study, serum samples were obtained from (60) Iraqis patients with end stage renal diseases (ESRD)on hemodialysis (HD) (30 patients with T2DM (G2) and 30 patients withoutT2DM (G3)) in addition to (30) healthy individuals as a control group (G1), their ages ranged from (35-65) years. The patients attended the Al-Yarmouk Teaching Hospital, Baghdad. Results: the results in this study showed a highly a significant elevation inserum angiopoietin li

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Publication Date
Sat Jan 01 2022
Journal Name
Computer Networks, Big Data And Iot
A Comprehensive Study of Various DC Faults and Detection Methods in Photovoltaic System
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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Detection of Some Active compounds and Vitamins Increasing in Aloe vera Callus culture
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This study was aimed to use plant tissue culture technique to induce callus formation of Aloe vera on MS. Medium supplied with 10 mg/l NAA and 5 mg/l BA that exhibit the best results even with subculturing. As the method of [1] 1g. dru weight of callus induced from A. vera crown and in vivo crown were extracted then injected in HPLC using the standards of Ascorbic acid (vit. C), Salysilic acid and Nicotenic acid (vit. B5) to compare with the plant extracts. Results showed high potential of increasing some secondary products using the crown callus culture of A. vera as compared with in vivo crown, Ascorbic acid was 1.829 ?g/l in in vivo crown and increased to 3.905 ?g/l crown callus culture . Salysilic acid raised from 3.54 ?g/l in in vivo c

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Publication Date
Thu Jul 25 2019
Journal Name
Journal Of Plant Protection Research
First report of phytoplasma detection on sand olive, cowpea and alfalfa in Iraq
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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