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Two-Stage Classification of Breast Tumor Biomarkers for Iraqi Women
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Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are further classified into either malignant or benign. The collected 20 breast cancer features are utilized to test the performance of the proposed classification system with Leave-One-Out (LOO) cross validation and Synthetic Minority Over-Sampling Technique (SMOTE) to balance the classes. Furthermore, correlation-based feature selection (CFS) was employed in an exploratory analysis to find the best features for the 2-stage classification system.

Results: Classification accuracy of 94% for stage-1 and 100% for stage-2was achieved with a Naïve Bayesclassifier which outperformed other three methods. In addition, CFS selected small subset of features as being the best five features out of the all 20 features for both stage-1 and stage-2.

Conclusion: We achieved a high classification accuracy which is promising to help improve the early diagnosis of breast tumor. The outcome of this study also shows the importance of CA15-3protein in saliva and blood as well as carcinoembryonic antigen level and total protein in blood, and Estrogen hormone level in saliva, for predicting breast tumors.

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Data And Network Science
The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

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Publication Date
Mon Mar 23 2020
Journal Name
Baghdad Science Journal
Molecular Modeling and in Silico Characterization of a Pathogenesis-Related Protein-10 (PR10) and its Coding Genes in some Oryza Species
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Rice is a major staple food for more than two thirds of the world population. Pathogenesis-related proteins-10 (PR10) have a range of 154 to 163 amino acid with molecular weight ~ 17 kDa.  They are acidic and generally intracellular and cytosolic proteins accumulate in plants in response to biotic and abiotic stresses. In the present study, a PR10 gene and its corresponding protein were characterized in O. sativa, O.  barthii, O. glaberrima, O. glumipatula, O. meridionalis, O. nivara, O. rufipogon and  O. punctata. The results revealed a narrow range of variation at both DNA and protein levels in all examined species except O. glumipatula. The latter showed a relatively

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Bacillus cereus in Meat Products: 16S rRNA Phylogenetic Tree analysis and Antimicrobial Investigation of Nisin A, Rosemary Essential Oil and Tetracycline
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Determination of Nickel and Cobalt in Cosmetic Products Marketed in Iraq Using Spectrophotometric and Microfluidic Paper-based Analytical Device (µPADs) Platform
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Two quantitative, environment-friendly and easily monitored assays for Ni (II) and Co (III) ions analysis in different lipstick samples collected from 500-Iraqi dinars stores located in Baghdad were introduced. The study was based on the reaction of nickel (II) ions with dimethylglyoxime (DMG) reagent and the reaction of cobalt (III) ions with 1-nitroso-2-naphthol (NN) reagent to produce colored products. The color change was measured by spectrophotometric method at 565 nm and 430 nm for Ni and Co, respectively, with linear calibration graphs in the concentration range 0.25-100 mg L-1 (Ni) and 0.5-100 mg L-1 (Co) and LOD and LOQ of 0.11 mg L-1 and 0.36 mg L-1 (Ni), and 0.15 mg L-1 an

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Publication Date
Mon May 01 2023
Journal Name
Chemical Engineering Research And Design
Treatment of petroleum refinery wastewater by electrofenton process using a low cost porous graphite air-diffusion cathode with a novel design
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Publication Date
Wed Jan 01 2020
Journal Name
Indian Journal Of Forensic Medicine And Toxicology
Continuous Flow Injection Analysis,Turbidmetric and Photometric Determination of Methyldopa Using a New Long Distance Chasing Photometer (NAG-ADF-300-2)
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A specific, sensitive and new simple method was used for the determination of methyldopa in pure and pharmaceutical formulations by using continuous flow injection analysis. This method is based on formation of ion pair compound between methyldopa and potassium hexacyanoferrate in acidic medium to obtain a yellow precipitate complex using long distance chasing photometer (NAG-ADF-300-2). The linear range for calibration graph was 0.05-35 mmol/L for cell A and 0.05-25 mmol/L for cell B, and LOD 1.4292 µg /200 µL for both cells with correlation coefficient (r) 0.9981 for cell A and 0.9994 for cell B, RSD% was lower than 0.5 % for n=8 for. The results were compared with classical method UV-Spectrophotometric at λ max=280 nm and turbi

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Water Process Engineering
Biochemical performance modelling of non-vegetated and vegetated vertical subsurface-flow constructed wetlands treating municipal wastewater in hot and dry climate
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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Measurement of Serum Trace Elements (Zinc, Copper, Magnesium and Iron) Concentrations in Pediatric Patients with Otitis Media with Effusion in Iraq
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Otitis media with effusion (OME) is a common disease especially among young children (before school age) and it is one of the common causes of acquired hearing loss in childhood. Pediatric patients with OME are usually undernourished. The purpose of this study is to determine whether the serum levels of trace elements (zinc, copper, magnesium, iron) have a role in the development of OME in children. This study carried out on 55 children and subdivided them into two groups. Group 1 (patient group) consist of 30 children suffering from OME and group 2 (control group) included 25 apparently healthy children. Serum levels of zinc, copper, magnesium and iron were measured for both groups. Comparison the results between the two groups showed t

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Detection, purification and characterization of a bacteriocin produced by Bacillus subtilis NK16 exhibits a significant antimicrobial activity against clinical Staphylococcus spp.
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Bacteriocin is an important antimicrobial peptide that can be used in industrial and medical fields due to its characteristics of antibacterial, food preservation and anticancer activities. Fifty isolates of Bacillus sp were collected from different soil samples which were already recognized via morphological and biochemical identification process. The isolates were screened for bacteriocin production effective against Staphylococcus spp in order to select the highest producing isolate. The isolate NK16 showed the maximum bacteriocin production (80 AU/ml) which was further characterized as Bacillus subtilis NK 16 through using API identification system (API 20E and API 50CHB). Then, next step was to detect the optimal conditions for maximum

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Publication Date
Sun Jan 01 2023
Journal Name
Material Science And Semiconductor Processing
Photocatalytic degradation of Congo red dye using magnetic silica-coated Ag2WO4/Ag2S as Type I heterojunction photocatalyst: Stability and mechanisms studies
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In the present study, magnet silica-coated Ag2WO4/Ag2S nanocomposites (FOSOAWAS) were fabricated via a multistep method to address the drawbacks related to single photocatalysts (pure Ag2WO4 and pure Ag2S) and to clarify the significant influence of semiconductor heterojunction on the enhancement of visible-light-driven organic degradation. Different techniques were performed to investigate the elemental composition, morphology, magnetic and photoelectrochemical properties of the fabricated FOSOAWAS photocatalyst. The FOSOAWAS photocatalyst (1 g/L) exhibited excellent photodegradation efficiency (99.5%) against Congo red dye (CR = 20 ppm) after 140 min of visible-light illumination. This result confirmed the ability of the heterojunction be

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