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

Immunosuppressive cytokines are the main components of the tumor microenvironment and perform a vital function in controlling the immune response to malignant neoplasms.The objective: to study the influence of interleukin-4 (IL-4) and transforming growth factor-β3 (TGF-β3) on the development of breast tumors in women.Materials and methods. The concentration of cytokines IL-4 and TGF-β3 in blood serum was determined in 40 women with benign breast tumors, 40 women with malignant breast tumors, and 40 healthy patients without breast pathology, who were included in the control group.Breast cancer (BC) patients were divided into two groups; the first group included patients with the II stage of BC, who were considered to have a low le

     New chelating ligand derived from triazole and its complexes with metal ions Rhodium, Platinum and Gold were synthesized. Through a copper (I)-catalyzed click reaction, the ligand produced 1,3-dipolar cycloaddition between 2,6-bis((prop-2-yn-1-yloxy) methyl) pyridine and 1-azidododecane. All structures of these new compounds were rigorously characterized in the solid state using spectroscopic techniques like: 1HNMR, 13CNMR, Uv-Vis, FTIR, metal and elemental analyses, magnetic susceptibility and conductivity measurements at room temperature, it was found that the ligand acts as a penta and tetradentate chelate through N3O2, N2O2, and the geometry of the new complexes are identified as octahedral for (Rh & Pt) complexes a

     New chelating ligand derived from triazole and its complexes with metal ions Rhodium, Platinum and Gold were synthesized. Through a copper (I)-catalyzed click reaction, the ligand produced 1,3-dipolar cycloaddition between 2,6-bis((prop-2-yn-1-yloxy) methyl) pyridine and 1-azidododecane. All structures of these new compounds were rigorously characterized in the solid state using spectroscopic techniques like: ¹HNMR, ¹³CNMR, Uv-Vis, FTIR, metal and elemental analyses, magnetic susceptibility and conductivity measurements at room temperature, it was found that the ligand acts as a penta and tetradentate chelate through N₃O₂, N₂O₂, and the geometry of the new complex

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

In Iraq, breast cancer incidence exceeds any other type of cancers and the etiology not understood well.Epstein Barr virus is a gamma herpesviruses and one of carcinogenic viruses that may implicated tobreast carcinogenesis. The nuclear antigen-1 (EBNA-1) protein is the sole EBV antigen that presentedin all tumors related to EBV and plays pivotal roles in carcinogenesis of the virus. Examination appliedby immunohistochemistry (IHC) to detect and demonstrate the correlation between (EBNA-1) and tumorsuppressor protein (P53) expression. The study includes paraffin-embedded tissue blocks of ninety 90malignant breast tissues and thirty 30 normal breast autopsies. EBNA-1 was significantly expressed in 40/90(44.4%) of malignant tissues wh