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Nanovaccines in cancer immunotherapy: Focusing on dendritic cell targeting
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Publication Date
Fri Sep 14 2018
Journal Name
Radiation Effects & Defects In Solids
Effect of gamma and beta radiation on I–V characterization of the solar cell panel
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Optoelectronic devices, widely used in high energy and nuclear physics applications, suffer severe radiation damage that leads to degradations in its efficiency. In this paper, the influence of gamma radiation (137Ce source) and beta radiation (90Sr source) on the photoelectric parameters of the Si solar cell, based on the I–V characterization at different irradiation exposer, has been studied. The penetrating radiation produces defects in the base material, may be activated during its lifetime, becoming traps for electron–hole pairs produced optically and, this will, decrease the efficiency of the solar cell. The main objective of the paper is to study and measure changes in the I–V characteristics of solar cells, such as efficienc

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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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Publication Date
Fri May 25 2018
Journal Name
Open Public Health Journal
Comparative Study on the Clinicopathological Profiles of Breast Cancer Among Iraqi and British Patients
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Background: Breast cancer is the most common cancer in Iraq and the United Kingdom. While the disease is frequently diagnosed among middleaged Iraqi women at advanced stages accounting for the second cause of cancer-related deaths, breast cancer often affects elderly British women yielding the highest survival of all registered malignancies in the UK. Objective: To compare the clinical and pathological profiles of breast cancer among Iraqi and British women; correlating age at diagnosis with the tumor characteristics, receptor-defined biomarkers and phenotype patterns. Methods: This comparative retrospective study included the clinical and pathological characteristics of (1,940) consecutive female patients who were diagnosed with invasive b

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Publication Date
Sat Oct 01 2022
Journal Name
The Egyptian Journal Of Hospital Medicine
The Effects of Soft Laser on Some Blood Parameters of Patients with Breast Cancer
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Background: Soft Laser has been advantageous in medical applications and is widely used in clinical practice. It is applied because it doesn’t cause the significant thermal effects or tissue hurt when irradiated. The blood response to low power laser radiation provides information about processes of laser radiation interaction with live creatures. Objective: The aim of the current work was to evaluate the laser-induced changes of in vitro erythrocyte sedimentation rate (ESR), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC) in patients with breast cancer by irradiating a human blood sample using a green laser and comparing its effects before and after irradiation with the same power density (100mW/c

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Modeling of Monocrystalline PV Cell Considering Ambient Conditions in Baghdad City
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Abstract

 

The environmental conditions are important factors, because they affect both the efficiency of a photovoltaic module and the energy load. This research was carried out experimentally and modeling was done in MATLAB –Simulink by monitoring the variation in power output of the system with environmental conditions such as solar radiation, ambient temperature, wind speed, and humidity of Baghdad city. From the results, the ambient temperatures are inversely proportional to humidity and the output power performance of the system, while the wind speed is directly proportional with the output power performance of the system.  

 

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Publication Date
Wed Sep 11 2019
Journal Name
Al-kindy College Medical Journal
Awareness of breast cancer among university female students in Baghdad
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Background: Breast cancer still a major cause of disability and mortality among women throughout the world. Lack of awareness and early detection programs in developing countries is a main reason for escalating the mortality.

Objectives: to assess level of awareness about breast cancer among university female students in Baghdad focusing on knowledge of breast cancer risk factors, warning symptoms and signs and knowledge about the screening method specially breast self-examination.

Methods: A cross-sectional study conducted over two months from first of march through April 2015 and included (240) female students in non- medical colleges at Al-Rusafa and A

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Publication Date
Tue Dec 01 2015
Journal Name
International Journal Of Current Microbiology And Applied Sciences
Expression Analysis of Salivary Microrna-31 in Oral Cancer Patients
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Oral carcinoma is the 6th most common cancer in the world. MicroRNAs are small non-coding single stranded RNAs. They have been shown to be capable of altering mRNA expression; thus some are oncogenic or tumor suppressive in nature. The salivary microRNA-31 has been proposed as a sensitive marker for oral malignancy since it was abundant in saliva more than in plasma. A total of 55 whole saliva samples were collected from 35 cases diagnosed with OC their ages and gender matched with 20 healthy subjects. TaqManq RT-PCR was performed for RNA samples. Mean age was 52.23+13.73 years in cases (range:17-70 years) with male predominance represented 69%. Risk of smoking and alcoholism was highly significant. The median fold change of miR-31 was sign

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Publication Date
Sat Jun 19 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Alteration of Serum Immunoglobulin Levels in Woman with Ovarian Cancer
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Ovarian cancer has a high mortality and delayed diagnosis. Several immunological alterations take place during ovarian carcinogenesis, and can be of value in the surveillance of the diseases. This research was conducted to evaluate serum immunoglobulin levels in women with ovarian cancer and to assess their role in disease process. The present study is composed of 85 women (mean age = 62.03±12.4 yrs) with clinically and pathologically confirmed ovarian cancer and 65 healthy females as a control group (mean age = 61±12.1 yrs). ELISA test was achieved for the determination of serum [IgG, IgA, IgM]. The findings of current study illustrated significant (P=0.001) increase in serum IgG, IgA, and IgM levels as compared to co

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Publication Date
Fri Jan 01 2021
Journal Name
Materials Today: Proceedings
In silico analysis of quercetin as potential anti-cancer agents
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