BACKGROUND: Breast cancer remains the most common malignancy among the Iraqi population. Affected patients exhibit different clinical behaviours according to the molecular subtypes of the tumour. AIM: To identify the clinical and pathological presentations of the Iraqi breast cancer subtypes identified by Estrogen receptors (ER), Progesterone receptors (PR) and HER2 expressions. PATIENTS AND METHODS: The present study comprised 486 Iraqi female patients diagnosed with breast cancer. ER, PR and HER2 contents of the primary tumours were assessed through immunohistochemical staining; classifying the patients into five different groups: Triple Negative (ER/PR negative/HER2 negative), Triple Positive (ER/PR positive/HER2 positive), Luminal A (ER

The aim of the research is to know the characteristics of both variables in order to be able the to construct the integrated framework of its paragraphs through the available information on both inspirational leadership and organizational health. as fundamental variables of research,  as well as the extent of the influence of the inspirational variable as an independent variable in the  organizational health variable as a variable in its three  physical, mental and social dimensions. The research is important to stimulate the behavior side of the staff. Which is one of the top concerns of senior management in the ministry, because of its great importance in increasing the effectiveness of the  performance of e

     Systemic lupus erythematosus (SLE) is a chronic autoimmune inflammatory disease with unknown etiology, though genetic and environmental factors appear to play a role in its pathogenesis. In particular, infectious processes are linked to the onset and exacerbation of SLE. The aim of the current study was to understand the relationship between some biochemical factors in SLE patients. 105 blood samples from both genders were collected.  ELISA technique was used for detecting specific procalcitonin, vitamin D and calcium. The results of this study showed that SLE patients recorded the lowest percentages of calcium (7.36 ± 0.10 mg/dl) than control (11.97 ± 2.12 mg/dl), and vitamin D (7.79 ± 0.58 pg/ml) than control (22.10 ± 4.8

Background: Hand, foot, and mouth disease is viral disease caused commonly by coxsackie virus A₁₆ virus. It is a mild disease and children usually recover with no specific treatment within 7 to 10 days. Rarely, this illness may be associated with aseptic meningitis were patient may need hospitalization.

Objective: To determine significance of clinical features of hand, foot and mouth disease.

Methods: A cross sectional study of cases with clinical features of hand, foot and mouth disease visiting the dermatological consultation unit of Al Kindy teaching hospital. Sampling was for Zyona and Edressi Quarter patients over the period of 1^st December 2017

Meta-heuristic algorithms have been significantly applied in addressing various real-world prediction problem, including in disease prediction. Having a reliable disease prediction model benefits many parties in providing proper preparation for prevention purposes. Hence, the number of cases can be reduced. In this study, a relatively new meta-heuristic algorithm namely Barnacle Mating Optimizer (BMO) is proposed for short term dengue outbreak prediction. The BMO prediction model is realized over real dengue cases data recorded in weekly frequency from Malaysia. In addition, meteorological data sets were also been employed as input. For evaluation purposes, error analysis relative to Mean Absolute Percentage Error (MAPE), Mean Square Err

Aims: The aim of this study was to evaluate the value and accuracy of longitudinal strain in detection of coronary artery disease compared to coronary angiography. Results: The left ventricular longitudinal strain-speckle tracking showed evidence of stenosis of left anterior descending artery, circumflex artery and right coronary artery in (86.1%), (76.4%), and (84.7%) respectively. For the stenosis in left anterior descending artery, the current study showed that the longitudinal strain was a good predictor for presence of significant stenosis with a sensitivity of (93.8%), specificity (75%) and accuracy (91.7%) compared with coronary angiography. For the stenosis in right coronary artery, the left ventricular longitudinal strain had

In this paper, an eco-epidemiological model with media coverage effects is established and studied. An -type of disease in predator is considered.  All the properties of the solution of the proposed model are discussed. An application to the stability theory was carried out to investigate the local as well as global stability of the system. The persistence conditions of the model are determined. The occurrence of local bifurcation in the model is studied. Further investigation of the global dynamics of the model is achieved through using a numerical simulation.

The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac