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Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum error rate, and the test maximum accuracy for K_value selection with an accuracy of 86.24%. Where the distance metric has been assigned using the Euclidean approach. From previous models, it seems that Breast Cancer Grade2 is the most prevalent type. For the future perspective, a comparative study could be performed to compare the supervised and unsupervised data mining algorithms.

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Publication Date
Mon Sep 29 2025
Journal Name
Journal Of Economics And Administrative Sciences
The impact of strategic foresight on strategic decision-making- Analytical study at the Ministry of Higher Education and Scientific Research
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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Involvement of Total Antioxidant Activity and eNOS Gene rs1799983/ rs2070744 Polymorphisms in Breast Carcinogenesis
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Globally, breast cancer is the common malignancy affecting women and understanding its associated molecular events could help in disease prevention and management strategies. The present study was set to investigate an association between total antioxidant capacity (TAC) and endothelial nitric oxide synthase (eNOS) polymorphisms with breast cancer. For this purpose, 100 subjects were participated in this work, including 50 female patients diagnosed with breast cancer recruited from Oncology hospital, Baghdad - Iraq and 50 healthy women as a control group. The concentration of antioxidants was measured in the serums collected from blood samples of breast cancer patients and healthy controls. While eNOS SNPs (rs1799983, G894T and rs2070744, T

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Biomarker Significance of Serum CXCL8, CXCL10 and CXCL16 in Breast Tumors of Iraqi Patients
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The biomarker significance of three chemokines (CXCL8, CXCL10 and CXCL16) was evaluated in sera of 45 breast cancer (BC) and 28 benign breast lesion (BBL) patients, as well as 20 control women. Clinical stage and tumor expression of estrogen (ER), progesterone (PgR) and human epidermal growth factor receptor-2 (HER-2) receptors were considered in this evaluation. The results demonstrated that CXCL8, CXCL10 and CXCL16 showed a significant increased median in BC and BBL patients compared to control (CXCL8: 47.3 and 25.7 vs. 15.0; CXCL10: 37.6 and 30.7 vs. 13.1; CXCL16; 27.9 and 25.2 vs. 19.2 pg/ml, respectively). The increased levels of CXCL8 and CXCL16 were more pronounced in triple-negative and HER-2 positive p

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Detection of Physical and Chemical Parameters Using Water Indices (NDWI, MNDWI, NDMI, WRI, and AWEI) for Al-Abbasia River in Al-Najaf Al-Ashraf Governorate Using Remote Sensing and Geographic Information System (GIS) Techniques
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The purpose of this study was to find out the connection between the water parameters that were examined in the laboratory and the water index acquired from the examination of the satellite image of the study area. This was accomplished by analysing the Landsat-8 satellite picture results as well as the geographic information system (GIS). The primary goal of this study is to develop a model for the chemical and physical characteristics of the Al-Abbasia River in Al-Najaf Al-Ashraf Governorate. The water parameters employed in this investigation are as follows: (PH, EC, TDS, TSS, Na, Mg, K, SO4, Cl, and NO3). To collect the samples, ten sampling locations were identified, and the satellite image was obtained on the

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Publication Date
Sun Jun 30 2024
Journal Name
Romanian Medical Journal
Serum and urine apolipoprotien A1 (ApoA1) as biomarkers in bladder cancer
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Bladder cancer (BC) is the predominant malignant neoplasm in the urinary system and ranks as the tenth most prevalent malignant tumor worldwide. Compared with females, males displayed a four-fold more common incidence of bladder cancer. It mainly affects men. Bladder cancer is the fourth most prevalent neoplasm in males. The most important protein that makes up high density lipoprotein (HDL), ApoA-I apolipoprotein A1 is essential in regulating the right amount of cholesterol. Multiple inquiries have demonstrated that APOA1 plays a pivotal role in the progression, infiltration, and spread of tumors. Objectives. The objective of this study was to measure the level of urine to serum apolipoprotein A1 in patients suffering from bladder

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
The role of Adipocytokines, Vitamin D, and C in Colorectal Cancer
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Colorectal cancer is the world's 3rd most frequent malignant neoplasm and the 4th most common cancer in Iraq. Leptin and Adiponectin are two major Adipocytokines produced by adipose cells that have opposite effects on the formation of colorectal tumors. Leptin induces tumor growth and metastasis, whereas Adiponectin inhibits it. 1,25-Dihydroxyvitamin D controls and limits cancer cell proliferation, differentiation, and survival. Vitamin C deficiency, on the other hand, has been regularly detected in cancer tissues and has potent anti-cancer properties. The purpose of this study was to look at the biochemical role of circulatory Adipocytokine levels (Adiponectin and Leptin) as well as the anti-cancer potentials of Vi

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Publication Date
Sun Mar 13 2011
Journal Name
Baghdad Science Journal
Bacteriological and Cytological study For bronchial washes from lung cancer patients
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The study included the collection of 75 bronchial wash samples from patients suspected to have lung cancer. These samples were subjected to a diagnostic cytological study to detect the dominant type of lung cancer. It was noticed that 33 patients proved to have a lung cancer out of 75 (44%) of these, 19 cases (57.6%)were diagnosed having Squamus cell carcinoma,7cases (21.21%) showed Adenocarcinoma ,6 cases (18.18%) were having small cell carcinoma while only one case (3.03%)was large cell carcinoma .Nearly 70% of cases were correlated with smokers .Bacteria were isolated from 53 patients in which 33 isolates were associated with the cancer cases while 20 of them from non infected patients. By using different morphological ,biochemical test

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Publication Date
Tue Oct 18 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 image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify 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 specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

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Publication Date
Fri Mar 23 2018
Journal Name
Entropy
Methods and Challenges in Shot Boundary Detection: A Review
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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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