KE Sharquie, AA Noaimi, BO Saleh, ZN Anbar…, Saudi Med J, 2009 - Cited by 13

The second most commonly diagnosed cancer is colorectal cancer (CRC) is in female. The levels of progranulin, obestatin and liver enzymes including ALT, AST and ALP were measured in forty five sera in female patients suffering from CRC before chemotherapy initiation treatment as G1, G2 after first chemotherapy cycle and G3 after second chemotherapy cycle compared with thirty female as a healthy control G4. Results showed a high significant increased in progranulin concentration and a high significant decrease in obestatin in G2 than other groups. The correlation between progranulin and ALP was a significant negative (-ve) relation while obestatin with AST gave a significant positive (+ve) correlation in G. The results also showed non signif

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

خلفية البحث: مرض السكري هو عامل خطر لأمراض القلب والأوعية الدموية وتصلب الشرايين وسبب مهم للوفاة. يرتبط خلل الدهون في الدم بشكل شائع بمرض السكري من النوع الثاني ويعتبر مؤشر تصلب الشرايين في البلازما علامة قوية للتنبؤ بخطر الإصابة بتصلب الشرايين وأمراض القلب التاجية. الهدف من البحث: دراسة ارتباط المؤشرات الدهنية لتصلب الشرايين لدى المرضى العراقيين المصابين بالسكري من النوع الثاني ولديهم أمراض قلبية وعائ

Background: Hypertension is a chronic medical condition in which the blood pressure in the arteries is elevated, it's classified as either primary (essential) hypertension or secondary hypertension, and it increases the risk of ischemic heart disease, peripheral vascular disease and other cardiovascular diseases. Several classes of medications collectively referred to as antihypertensive drugs like beta blockers, calcium channel blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers, renin inhibitors and statins (HMG-CoA) reductase inhibitor. Statin medication may have some beneficial effects when subjects have dental plaque or signs of periodontitis as gingival bleeding. The purpose of this study were to as

Focal adhesion kinase (FAK), ephrin receptor type A4 (EphA4), and adiponectin (ADPN) are important indicators in inflammation, tumor growth, migration, and angiogenesis in some cancers. The predictive impact of their concentrations in acute myeloid leukemia (AML) patients to be identified remains. The research sought to explore the effect of FAK, EphA4, and ADPN as prognostic biomarkers, and their influence on patient survival, and to look for any potential correlation between their levels with hematological parameters in AML patients.

Introduction: Rheumatoid arthritis (RA) is one of the most prevalent systemic inflammatory diseases worldwide. Cardiac complications present the most common mortality cause among RA patients. One of the most important comorbid conditions with RA is diabetic hyperglycemia mainly type 2 diabetes mellitus (T2DM). Aim of the study: The present study was conducted to assess prevalence of T2DM among patients diagnosed with RA from Iraq. Methodology: We included a randomly selected 100 rheumatoid arthritis. All included patients were subjected to anthropometric measurements, diabetic profile assessment and ESR, CRP and rheumatoid factor measurement. Results: Among the included RA patients, 28 patients were diagnosed with new-onset DM. Our

<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