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ULTRA-WIDEBAND FEATURING ENHANCED DELAY AND SUM ALGORITHM AND ORIENTED FOR DETECTING EARLY STAGE BREAST CANCER
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Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, the proposed algorithm is effective in reducing the clutter and producing better images. Overall, the methods and procedures registered a signal-to-clutter ratio (SCR) value of 1.54 dB when imaging the most challenging example involving the heterogeneously dense model in 8-antenna geometry

Publication Date
Tue Aug 15 2023
Journal Name
Journal Of Economics And Administrative Sciences
Machine Learning Techniques for Analyzing Survival Data of Breast Cancer Patients in Baghdad
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The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

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Publication Date
Tue Feb 26 2019
Journal Name
Journal Of Contemporary Medical Sciences
Demographic and clinical profiles of female patients diagnosed with breast cancer in Iraq
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Objective To highlight the main demographic characteristics and clinical profiles of female patients registered with breast cancer in Iraq; focusing on the impact of age.Methods This retrospective study enrolled 1172 female patients who were diagnosed with breast cancer at the Main Center for Early Detection of Breast Cancer/Medical City Teaching Hospital in Baghdad. Data were extracted from an established information system, developed by the principal author under supervision of WHO, that was based on valid clinical records of Iraqi patients affected by breast cancer. The recorded information regarding clinical examination comprised positive palpable lumps, bloody nipple discharge, skin changes, bilateral breast involvement, tumor

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Advanced Pharmaceutical Technology & Research
Hesperetin effect on MLH1 and MSH2 expression on breast cancer cells BT-549
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Publication Date
Tue Jun 21 2022
Journal Name
Analytical Science & Technology
The whole wheat effect and refined with E-selectin polymorphism on breast cancer
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Wheat is rich in sources of fiber, oligosaccharides, and resistant starch, simple carbohydrates which may have a protective role against carcinoma. Additionally, Whole wheat/bran as well includes contains phytochemicals such as flavonoids, lignans, folate, phytosterols, phenolic acids, and tocols. The above phytochemicals suitable forms antioxidant and cholesterol-reducing activities. Phytoestrogens are regarded as especially essential in the preventative measures of hormonally dependent malignancies such as breast cancer (BC). In this study lowered BC risk has been associated with whole grain/bran consumption with an odds ratio (OR=0.24 and 95 %CI=0.10-0.56). Wheat/bran appears to have a reliable protective impact against BC. While intake

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Publication Date
Mon Dec 25 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Knowledge, Attitudes and Barriers Towards Breast Cancer Health Education Among Iraqi Community Pharmacists
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With the increasing prevalence of breast cancer among female internationally, occupies about 25% of all cases of cancer, with a measured 1.57 million up to date cases in 2012. Breast cancer has turn a most warning to health of female in Iraq, where it is the major cause of death among women after cardiovascular diseases, with a mortality rate of 23% related cancer. Recently there is a crucial requirement to include community pharmacists in health elevation activities to support awareness and early diagnosis of cancer, specially breast cancer. The aim of this study is to assess knowledge, attitude and perceived barriers amongst Iraqi community pharmacists towards health promotion of breast cancer. This study is cross sectional research. A

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Publication Date
Tue Jul 07 2015
Journal Name
European Chemical Bulletin
DETERMINATION OF CANCER ANTIGEN CA15-3 AND ALPHA FETO PROTEIN (AFP) LEVELS AS TUMOR MARKER IN PATIENTS WITH BREAST AND PROSTATE CANCER
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European Chemical Bulletin (ISSN 2063-5346) is a peer-reviewed journal that publishes original research papers, short communications, and review articles in all areas of chemistry. European Chemical Bulletin has eight sections, namely

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Publication Date
Mon Jan 01 2018
Journal Name
Research Journal Of Pharmacy And Technology
Molecular Genetic variability in the D-loop region for females with Breast Cancer and the effect of the Chemotherapy
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Information Engineering And Applications
Development of Prognosis Factors in a Scoring System for Predicting of Breast Cancer Mortality
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Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate

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Publication Date
Sun Dec 10 2017
Journal Name
Journal Of Pharmaceutical, Chemical And Biological Sciences
BRCA1 is Overexpressed in Breast Cancer Cell Lines and is Negatively Regulated by E2F6 in Normal but not Cancerous Breast Cells
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This study focused on the expression and regulation of BRCA1 in breast cancer cell lines compared to normal breast. BRCA1 transcript levels were assessed by real time quantitative polymerase chain reaction (RT-qPCR) in the cancer cell lines. Our data show overexpression of BRCA1 mRNA level in all the studied breast cancer cell lines: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 along with Jurkat, leukemia T-lymphocyte, the positive control, relative to normal breast tissue. To investigate whether a positive or negative correlation exists between BRCA1 and the transcription factor E2F6, three different si-RNA specific for E2F6 were used to transfect the normal and cancerous breast cell lines. Interestingly, strong negative relationship was found b

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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