Background: Breast cancer is the most frequently diagnosed malignancy and the second leading cause of mortality among women in Iraq forming 23% of cancer related deaths. The low survival from the disease is a direct consequence to the advanced stages at diagnoses. Aim: To document the composite stage of breast cancer among Iraqi patients at the time of diagnosis; correlating the observed findings with other clinical and pathological parameters at presentation. Patients and Methods: A retrospective study enrolling the clinical and pathological characteristics of 603 Iraqi female patients diagnosed with breast cancer. The composite stage of breast cancer was determined according to UICC TNM Classification System of Breast Cancer and the Ameri

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

The infection with H. Pylori stimulates a signaling cascade that causes the generation of Cytokines and provokes Oxidative stress that is involved in the chronic inflammatory response leads to Gastric cancers. Reactive oxygen species (ROS) produce 8-Hydroxydeoxyguanosine (8-OHdG), the persistent oxidative DNA damage product. The study objective was to assess if there was a link between inflammatory cytokine levels and the presence of Oxidative DNA damage in Gastric tumor patients. In addition, evaluation of the diagnostic and prognostic value of Oxidative DNA damage and inflammatory cytokine biomarkers for Stomach cancers is being conducted. The study was accomplished on medically diagnosed Stomach cancer patients before any form of trea

A case-control study was designed to find out the association between rs2234671 polymorphism of cxcr1 and rUTI in a sample of Iraqi women by polymerase chain reaction- sequence-specific primer (PCR-SSP) method. The current findings revealed that the genotype GC (OR= 7.86, 95% CI = 2.82-21.87, P= 7.7 × 10-5) and the C allele (OR= 3.93, 95% CI = 1.97 - 7.83, P = 9.8×10-5) are significantly associated with rUTI. However, the genotype GG played as a protective factor (OR= 0.12, 95% CI = 10.05 - 0.34, P = 4.0 ×10-5). Depending on these findings, the genotype GC is significantly associated with rUTI.

Here, a high sensitive method for biomarker identification according to nanostructure, using enzyme-linked immunosorbent assays (ELISAs), called Nano-ELISA, was presented. Different shapes of gold nanostructures (star and sphere; GNSs and GNPs) with a particle size of 40 nm for sphere particles were altered with a monoclonal antibody (Ab) as a detector Ab. To amplify the optical signal, gold nanostructures were employed as carriers of the signaling specific antibody against insulin growth factor binding protein- 3 (IGFBP-3). The substrate was catalytically oxidized by the Horseradish Peroxidase (HRP) conjugated gold nanostructure, and HRP also enhanced the optical signals, reflecting the amount of the targeting IGFBP-3. In comparison to t

<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

Breast cancer (BC) is the most prevalent tract cancer in the world, including Iraq. The classified breast tumors to benign, malignant, and radiotherapy. Cancer treatment depends on certain stages such as mastectomy then chemotherapy alone or with radiation therapy or endocrine therapy according to the prognostic features obtained from the pathology report. The present study included 100 females. The women were split into two groups, control group that consisted of 50 apparently healthy females and 50 patients with BC group who undergo the radiotherapy. The current study highlighted on some of the anthropometric measurements, including the oxidative stress index malondialdehyde (MDA), the concentrations of total antioxidant capacity (TAC), s