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

Afamin, which is a human plasma glycoprotein, a putative multifunctional transporter of hydrophobic molecules and a marker for metabolic syndrome. Afamin concentration have been proposed to have a significant role as a predictor of metabolic disorders. Since NAFLD is associated with metabolic risk factors, e.g., dyslipidemia, insulin resistance and visceral obesity, it is considered as the hepatic manifestation of the metabolic syndrome. The objective of this study is to determine Afamin levels in hypothyroid patients with and without fatty liver disease and compare the results with controls. Also to study the relationship of Afamin level with the Anthropometric and Clinical Features (Age, Gender, BMI and Duration of Hypothyroidism) , Serum

Background: Acute coronary syndrome (ACS) is a common disease, and a major determinant of morbidity and mortality in all races. The pleiotropic effects of the receptor activator of nuclear factor-kappa B ligand (RANKL) such as modulation of cell survival, mineralization and inflammation, make it an interesting candidate mediator in the progression and destabilization of atherosclerotic lesions.Objectives: This study was performed to investigate the role of RANKL in the pathogenesis of ACS.Methods: The levels of RANKL were measured by ELISA method in sera of 60 ACS patients, 31 patients with unstable angina (UA) and 29 patients with myocardial infarction (MI) in comparison with 20 apparently healthy controls.Results: Current data indicate

Anaemia is a crucial issue among cancer patients and need to be treated properly. High incidence of anaemia in patients with cancer have been associated with several physiological manifestations, leading to decreased quality of life (QOL).

The current study aimed to assess the severity of anaemia, evaluate the current treatment guideline of anaemia, and to determine the association between the level of anaemia and its treatment on quality of life of breast cancer patients in Malaysia. This prospective study conducted among breast cancer patients in multicancer centers in Malaysia including three follow ups after receiving their chemotherapy. Clinical data were collected from their medical records and at each follow up, they asked

Background: Understanding the pathogenesis and molecular basis of Oral Squamous Cell Carcinoma (OSCC) has increased rapidly over the past few years that is essential to improve patient's prognosis and treatment modalities. The purpose of this study to evaluate the Immunohistochemical expressions of AKT, ATM, AND Cyclin E in oral squamous cell carcinoma Materials and methods: This study was performed on a forty formalin-fixed paraffin-embedded blocks which histopathologically diagnosed as Oral Squamous Cell Carcinoma. All cases were collected from the Histopathological Laboratory from patients treated surgically at Maxillofacial surgery Department at Ramadi Teaching Hospital, Iraq. Results: The immunohistochemical staining of AKT showed pos

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

Background: Multiple myeloma (MM) is characterized by clonal proliferation of malignant plasma cells within the bone marrow. In most patients, monoclonal immunoglobulin heavy chains or light chains are produced and are associated with organ dysfunction. The growth factor B-cell activating factor (BAFF) plays an important role in the pathogenesis of multiple myeloma due to its ability to promote B-cell survival, expansion, and differentiation. Objective:  to measure the circulatory level of B-cell activating factor in multiple myeloma patients in relapsed and remission states and explore its possible correlations with the clinical staging, β2-microglobulin, and interleukin-6. Methods: This cross-sectional study was performed on 60

Background: Breast cancer remains a substantial cause of morbidity and mortality, there is a need for continued efforts to understand the etiology of the disease, maintain screening effort, implement prevention strategies, and develop better treatments.Objective: To analyze the risk factors, improve early detection and prevention of breast cancer in Al-Russafa district- Baghdad, aiming to increase survival rate and improve the quality of life.Methods: A cross sectional audit of 258 breast cancer cases seen at Al-Elwiya maternity teaching hospital from January2009 to December 2011,data collected from patients files were: age, gender , residency, marital status, parity, age at menarche and menopause age at first live birth, hormonal therap

<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

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