Introduction: Breast cancer is the most common cancer and the major cause of cancer related deaths among Iraqi women. Due to the relatively late detection of breast cancer, the majority of the patients are still treated by modified radicle mastectomy. Aim: To assess the time lag between diagnosis of breast cancer and mastectomy among Iraqi patients; correlating the findings with other clinicopathological characteristics of the disease. Patients and methods: This retrospective study enrolled 226 Iraqi female patients who were diagnosed with breast cancer. Data were registered on the exact time period between signing the histopathological report and the surgical treatment. Other recorded variables included the age of the patients, their level

Breast cancer (BC) is first of the top 10 malignancies in Iraq. Dose‐volume histograms (DVHs) are most commonly used as a plan evaluation tool. This study aimed to assess DVH statistics using three‐dimensional conformal radiotherapies in BC in an adjuvant setting.

This paper delves into the significant role played by local social and traditional structures in shaping Traditional Community Tenure (TCT) within Iraqi Land Tenure Legislation (ILTR), and examines their impact on gender inequalities, with a specific focus on women's land tenure rights. The methodological approach employed in this study identified the sources of barriers to gender equality within TCT as outlined in ILTR at two different bilateral levels, with input obtained from key stakeholders in a selected city in Iraq. The case study survey encompassed three districts, which served as local layers within the historic sectors of the Iraqi city of Al-Nasiriya. the study employed quantitative methods, including a household surveyو with

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

<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

Objective: We hypothesized that attacking cancer cells by combining various modes of action can hinder them from taking the chance to evolve resistance to treatment. Incorporation of photodynamic therapy (PDT) with oncolytic virotherapy might be a promising dual approach to cancer treatment. Methods: NDV AMHA1 strain as virotherapy in integration with aminolaevulinic acid (ALA) using low power He-Ne laser as PDT in the existing work was examined against breast cancer cells derived from Iraqi cancer patients named (AMJ13). This combination was evaluated using Chou–Talalay analysis. Results: The results showed an increased killing rate when using both 0.01 and 0.1 Multiplicity of infection (MOI) of the virus when combined with a dose of 617

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

Background: The study's objective was to estimate the effects of radiation on testosterone-related hormones and blood components in prostate cancer patients. N Materials and Method: This study aims to investigate the effects of radiation on 20 male prostate cancer patients at the Middle Euphrates Oncology Centre. Blood samples were collected before and after radiation treatment, with a total dose of 60- 70 Gy, The blood parameters were analyzed. The hospital laboratory conducted the blood analysis using an analyzer (Diagon D-cell5D) to test blood components before and after radiation. Hormonal examinations included testosterone levels, using the VIDASR 30 for Multiparametric immunoassay system Results: The study assessed the socio-demogra