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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 calculated with risk mortality at 5 and 10 years depending on the number of unknown factors. The new system presented in a graphical user interface to facilitate the friendliness at the user side.

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Assessment of Health Beliefs Among Iraqi Breast Cancer Patients in Baghdad using either Tamoxifen or Trastuzumab
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Breast cancer is the most diagnosed form of malignant tumour in Iraqi women. Tamoxifen and trastuzumab are highly effective adjuvant therapy for breast cancer.

This study's objectives were to define the patient's belief in tamoxifen or trastuzumab when used as adjuvant therapy and to determine the variation in belief between the two medications in a sample of Iraqi breast cancer patients.

The cross-section survey was conducted using the BMQ-Specific questionnaire. Ninety-seven participants (sixty-seven tamoxifen, thirty trastuzumab) participated in this study.

The mean of specific-necessity scale for tamoxifen was (3.7) and for trastuzumab (4). The findings showed a high necessity for both medicines, and there wer

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Publication Date
Wed Mar 15 2023
Journal Name
Bionatura
Cytotoxic potential activity of quercetin derivatives on MCF-7 breast cancer cell line
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Many previous investigations have found quercetin to be a powerful antioxidant and antitumor flavonoid, but its poor bioavailability has limited its use. This current study investigated the effects of two newly synthesized Quercetin Schiff bases containing 2-amino thiadiazole-5-thiol (Q1), and its benzyl derivatives (Q2) on MCF-7 human breast cancer cells. Cell viability and apoptosis were assessed to determine the toxic effects of Q1 and Q2. Cytotoxicity valuation showed that both compounds inhibited MCF-7 cell growth, and lactate dehydrogenase (LDH) activity increased in a dose-dependent aspect compared to the control group. Comet assay results observed that Q1 and Q2 induce more serious DNA damage than the control (untreated cell

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Publication Date
Thu Mar 09 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Evaluation of Mg, Cu, Zn, Cr and Mn Concentrations in Iraqi patients’ female with Breast Cancer.
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To investigate the concentration and role of certain important elements in 30 patients women with breast cancer (without treatment, with treatment, and treated but recancer) by using statistical analysis. The serum concentration of some important elements (Mg, Cu, Zn, Cr, and Mn) of the patients with breast cancer, and (7) healthy control women it is found that: there is a significant increase in the concentration of (Mg, Zn, and Mn), but significant decrease in Cu concentration in all breast cancer patients compared with the healthy control. And significantly higher in Cr concentration in notreated and treated with recancer, but lower in treated patients as compared with healthy control.

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

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Publication Date
Mon Jun 01 2020
Journal Name
P J M H S
The influence of Breast Cancer Molecular Subtypes on Metastatic pattern in Iraqi patients
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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The In Situ Expression of IL-6 and IL-1? in breast cancer patients
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Breast cancer is the second most common cancer in women world. Multiple Cytokines appear to have a dominant role in human breast cancer formation. Estimation of the in situ expression of  IL-6 and IL-1β in breast cancer patients. A sixty patients with breast cancer BC were divided into two clinical subgroups, (30) with malignant breast cancer MBC and (30) with benign breast tumor as a control group according to histological examination. In situ hybridization technique used for detection of IL-6 and IL-1β mRNA sequence in two groups.  The results showed that percentages of mRNA expression of IL-6 and IL-1β were in (≥ 11-50%) for malignant breast cancer. This research also investigated that (73.3%) of beni

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Correlation between Serum and Tissue Markers in Breast Cancer Iraqi Patients
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Breast cancer is the most prevalent malignancy among women worldwide, in Iraq it ranks the first among the population and the leading cause of cancer related female mortality. This study is designed to investigate the correlations between serum and tissue markers in order to clarify their role in progression or regression breast cancer. Tumor Markers are groups of substances, mainly proteins, produced from cancer cell or from other cells in the body in response to tumor.  The study was carried out from April 2018 to April 2019 with total number of 60 breast cancer women. The blood samples were collected from breast cancer women in postoperative and pretherapeutic who attended teaching oncology hospital of the medical city in Baghdad and

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Sat Dec 02 2017
Journal Name
International Food Research Journal
Extraction and purification of cytotoxic compounds from Premna serratifolia L.(bebuas) for human breast cancer treatment.
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