Breast cancer is one of the comments malignant tumors worldwide especially in Iraq; it is a leading cause of death in Iraqi women. Determination of estrogen and progesterone receptors status is helpful in selecting the patients most likely to receive benefit from endocrine therapy, and provide prognostic information on recurrence and survival since their expression is related to the degree of the tumor differentiation. From November 2012 to March 2013, 150 breast cancer patients at Al-Amal Hospital in Baghdad were attended to start treatment of disease for the first time. All patients included in this study did not receive chemotherapy. Patients were asked to bring their paraffin embedded tissue blocks to participate in estrogen, progesterone and Her-2/nue receptors estimation. Blood samples were also collected from the patients to estimate positive Her-2nue cases in serum. Age distribution in women with breast cancer showed that 44%of cases at age group (40 – 49) years. 23% of the patients had a positive family history (first and second degree). Histological types of breast carcinoma showed that 82%, 14% and 4% were ductal, lobular and mixed carcinoma respectively. The Makee classification showed that Grade I, II, and III were detected in 10%, 64% and 26% respectively. TNM staging revealed that 16% of the patients were recorded in stage I, 44% in stage II, 32% in stage III and 8% in stage IV. It was demonstrated that 72% and 70% of breast carcinomas were positive for ER and PR respectively; both markers correlated with age, family history, type, histological grade and stage of the disease. Her-2/neu showed 28% expression in Iraqi breast cancer cases. HER2/neu over-expression (>15 ng/ml) was observed in 36 out of 150 patients (24%) Her-2/neu serum level at ELISA diagnosis and in 42 out of 150 (28%) at immunohistochemistry method (IHC).There were significant (P <0.001) association between tissue HER-2/neu and serum HER-2 levels. Detection Her-2/neu in serum by ELISA technique could be used as a method for detection with high rate reached to 78% after mastectomy, also it considered as an excellent method for follow up.
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This research adopts the estimation of mass transfer coefficient in batch packed bed distillation column as function of physical properties, liquid to vapour molar rates ratio (L / V), relative volatility (α), ratio of vapour and liquid diffusivities (DV / DL), ratio of vapour and liquid densities (ρV / ρL), ratio of vapour and liquid viscosities (μV/ μL).
The experiments are done using binary systems, (Ethanol Water), (Methanol Water), (Methanol Ethanol), (Benzene Hexane), (Benzene Toluene). Statistical program (multiple regression analysis) is used for estimating the overall mass transfer coefficient of vapour and liquid phases (KOV and KOL) in a correlation which represented the data fairly well.
KOV = 3.3 * 10-10
... Show MoreThis paper concerns with deriving and estimating the reliability of the multicomponent system in stress-strength model R(s,k), when the stress and strength are identical independent distribution (iid), follows two parameters Exponentiated Pareto Distribution(EPD) with the unknown shape and known scale parameters. Shrinkage estimation method including Maximum likelihood estimator (MLE), has been considered. Comparisons among the proposed estimators were made depending on simulation based on mean squared error (MSE) criteria.
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Missing data is one of the problems that may occur in regression models. This problem is usually handled by deletion mechanism available in statistical software. This method reduces statistical inference values because deletion affects sample size. In this paper, Expectation Maximization algorithm (EM), Multicycle-Expectation-Conditional Maximization algorithm (MC-ECM), Expectation-Conditional Maximization Either (ECME), and Recurrent Neural Networks (RNN) are used to estimate multiple regression models when explanatory variables have some missing values. Experimental dataset were generated using Visual Basic programming language with missing values of explanatory variables according to a missing mechanism at random general pattern and s
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Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati
Background: Globally, breast cancer is the second leading cause of death among women in Iraq. Several genetic and environmental factors are associated..
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Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had
... Show MoreThe research took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide practical evidence that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial and that includes all of the spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. The spatial analysis had been applied to Iraq Household Socio-Economic Survey: IHS
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