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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
Fri Feb 01 2013
Journal Name
Ijbpas
THE POSSIBLE RELATIONSHIP BETWEEN SERUM TUMOR NECROSIS FACTOR ALPHA LEVEL AND THE RECOVERY OF PATIENTS WITH PULMONARY TUBERCULOSIS
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Mycobacterium tuberculosis is the cause of the major world health issue, tuberculosis (TB). The cytokine, tumor necrosis factor alpha (TNF-α) has been implicated in protection against TB in the early stages of the disease. TNF-α is an effective cytokine in the killing of intracellular M. tuberculosis. This study inducted to investigate whether there is any relationship between levels of TNF-α in sera of TB patients and their recovery, and is there any difference in the level of this cytokine in sera of female and male TB patients. This study included 29 patients with pulmonary TB (18 female and 11 male), their ages ranging from 37 to 59 years. All of them received first line TB therapy. They were consulted at Pasture Center during Septem

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Publication Date
Sat Nov 10 2018
Journal Name
Oriental Journal Of Chemistry
New Series of Substituted Heterocyclics Derived from α , β – Unsaturated Ketone and Their Cytotoxic Activity Tumor Cell Lines
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The aldol condensation of 2-acetylnaphthalene with 9-anthracene carboxaldehyde afforded α, β-unsaturated keton (1) . New heterocyclic compounds containing: cyclohexenone[2], indazole[3], pyrimidinethion [4], thiazolo fused pyrimidine[5], isoxazoline[6], substituted pyrazoline[7]a-d and pyrimidinone[8] rings system were synthesized from α, β-unsaturated keton[1]. Cyclization of [1] with ethylacetoacetate gave the mentioned heterocycle cyclohexanone [2]. The cyclo condensation of [2] with hydrazine gave the new indazole derivative [3]. furthermore, the reation of [1]with thiourea gives thiopyrmidine derivative [4]. The cyclo condensation of [4] with chloroacetic acid gave the fused rings [5]. Then reacted compound[1] with hydroxy

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Biochemical study of glutathione reductase (GSH-Red) in Tissue Homogenate of Breast Tumors
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Breast tumor patients generally have more oxidative stress than normal females. This was clear from significant decrease (P<0.05) in tissue GSSG-Red activity. The study had found that free radicals in malignant breast tumors were higher than benign tumors, therefore the GSH- Red might be used as markers for prognosis of the disease. Results of molecular characterization show optimum enzyme concentration substrate conc., optimum pH, temperature & time & effect of some (chemotherapies in constant conectrations) for GSSG-Red activity.

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Isolation, Screening and Antibiotic Sensitivity of Pseudomonas species from Kelana Jaya Lake Soil in Selangor Malaysia
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Pathogenic microorganisms from hospitals, communities, and the environment remain great threats to human health. The increasing concern about antibiotic resistance has also necessitated the search for robust alternatives. Therefore, this study aims to isolate, screen and evaluate the antibiotic susceptibility of Pseudomonas aeruginosa isolated from a soil sample taken from northern, western and eastern parts of Kelana Jaya Lake against four antibiotics (gentamycin, tetracycline, ampicillin, and penicillin) on a Mueller-Hinton Agar media plate. Pseudomonas identification was done by using API 20 kit. Disc diffusion was employed as well as the oxidase test. From the positive oxidase result, the isolated bacteria were identified as Burkhold

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Relation between Serum Leptin, Lipid Profiles and other biomarkers levels in patients with type 2 diabetic nephropathy
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Background: In advanced diabetes mellitus, serum levels of the most hormones are altered due to several interplaying mechanisms. Objective: To assess the relation of serum leptin and lipid profile in type 2 diabetic nephropathy. Patients and Method: Serum leptin levels and its relation to lipid profile were estimated in 62 patients with type 2 diabetic nephropathy attending the National Diabetes Center in Al- Mustansiriya University, and (26) healthy individuals considered as control group. The diabetic patients were classified into three groups, (24) pathients with normoalbuminuria (21) patients with microalbuminuria and (17) patients with macroalbuminuria. Fasting plasma glucose, serum creatinine, Hb A1c %, lipid profile (Total c

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Publication Date
Tue Aug 27 2024
Journal Name
Diagnostics
Accuracy of Gingival Crevicular Fluid Biomarkers of MMP8, TIMP1, RANK, RANKL, and OPG in Differentiating Symptomatic and Asymptomatic Apical Periodontitis
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Apical periodontitis (AP) is the most prevalent chronic inflammatory disease of the teeth. Bone resorption dynamics in symptomatic and asymptomatic AP are still unrecognized. This study examined different inflammatory markers within gingival crevicular fluid, including matrix metalloproteinases 8 (MMP8), tissue inhibitors of metalloproteinases 1 (TIMP1), receptor activator of nuclear factor κB (RANK), its ligand (RANKL), and osteoprotegerin (OPG), to be used in comparing symptomatic apical periodontitis (SAP) and asymptomatic apical periodontitis (AAP) versus healthy teeth. Subjects with SAP, AAP, and a control group were recruited and GCF samples were collected by Periopaper strips. Clinical and radiographical measures were used f

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Publication Date
Fri May 12 2023
Journal Name
European Journal Of Dentistry
Salivary IL-17 and IL-10 as Potential Diagnostic Biomarkers of Different Stages of Periodontitis in Smoker and Nonsmoker Patients
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Abstract<p> Objectives The gold standard in the field of periodontal research currently is to find a valid biomarker that can reliably be used for diagnosing periodontal diseases. Given the limitations of the current diagnostic tools that stall to predict susceptible individuals and determine whether active tissue destruction is occurring, there is an increased urge to develop alternative diagnostic techniques that would compensate for the problems inherited in these available methods, such as measuring levels of biomarkers present in oral fluids such as saliva; so the aim of this study was to determine the diagnostic potential of interleukin-17 (IL-17) and IL-10 to differentiate periodontal health </p> ... Show More
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Publication Date
Wed Nov 05 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of orthodontic tooth movement on salivary levels of Interleukin-1beta, Tumor Necrosis Factor-alpha, and C- reactive protein
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Background: Orthodontic force is considered to stimulate cells in the periodontium to release many mediators such as cytokines which play a responsible role for periodontal and alveolar bone remodeling, bone resorption and new bone deposition. Aim of this study was carried out to estimate changes of the (interleukin-one beta, tumor necrosis factor – alpha and C-reactive protein) levels in unstimulated whole saliva during the leveling stage of orthodontic tooth movement. Materials and methods: The sample consisted of thirty adult patients (12 males and 18 females) with ages ranges (19-23) years. Each sample had Class I and Class II malocclusion dental classification and required bilateral extraction of their maxillary first premolars, und

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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Science, Technology And Engineering Systems Journal
Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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