The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The maximum potential and the character regression estimations were found in estimating the two-response logistic regression model by adopting the bootstrap method and comparing the estimations according to the standard mean squares of error (MSE).It was evident through comparison that the character regression method in estimating the two-response logistic regression model by adopting the bootstrap method is the best in estimating the logistic regression model parameters as it has less (MSE).
Human cytomegalovirus (HCMV) has a worldwide distribution and extremely common infections. The presence of HCMV genome and antigens has been detected in many kinds of human cancers especially breast cancer. In Iraq, the incidence of breast cancer generally exceeds any other type of malignancies among Iraqi population. The study was performed in the period between October 2016 and June 2017 in Central public health laboratory/Baghdad. It involve samples from 90 women including 60 breast cancer patients, 20 benign tumor patients, and 10 normal breast tissues. A blood sample was obtained from each woman included in this study. Anti-HCMV IgG antibody was presented in 9/10 (90%) of normal women, benign breast tumor patients 19/20 (95%) and malig
... Show MoreHuman Cytomegalovirus (HCMV) is an enveloped ubiquitous ds-DNA virus that has been implicated in several types of malignancies. The current work was conducted in the period extending from (November 2018 to the end of October 2019) and aimed to assess the frequency of glycoprotein N (gN) genotypes of HCMV. A total number of 91serum and plasma specimens were collected to fulfill this purpose from females (71 breast cancer patients, and a control group of 20 females) attending Al-Amal hospital for cancer management and Baghdad teaching hospital. The molecular part of this data was achieved through both PCR and Multiplex PCR for detection of HCMV gN (UL73) entire gene as well as for genotyping. gN was detected in 36/71 (50.7%) of breast cancer
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The prospective study has been designed to determine some biomarkers in Iraqi female patients with
breast cancer. The current study contained 30 patients whose tissue samples have been collected from
hospitals in Medical City in Baghdad after consent patients themselves and used immunohistochemical
technique to determine these markers. The results showed a significant correlation between ER and PR tissue
markers (Sig = 0.000) and a significant correlation between cyclin E phenotype and cyclin E intensity (Sig =
0.001).
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The risk of breast cancer development is believed to be attributed to the alterations of a number of key biological components. Within this context, elevated levels of some chemokines that act as growth factors and can promote cancer development. The current study was designed to evaluate CXCL3 (a chemokine C-X-C Motif Ligand 3) and leptin (a peptide hormone synthesized by adipose tissue with cytokine activity) serum of Iraqi breast cancer patients in comparison to healthy controls. A total of 90 participants consisted of 60 patients diagnosed with breast cancer and 30 healthy women as control group were enrolled into this case-control study. Venous blood samples were collected from all participants to evaluate CXCL3 and leptin serum levels
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The parametric programming considered as type of sensitivity analysis. In this research concerning to study the effect of the variations on linear programming model (objective function coefficients and right hand side) on the optimal solution. To determine the parameter (θ) value (-5≤ θ ≤5).Whereas the result، the objective function equal zero and the decision variables are non basic، when the parameter (θ = -5).The objective function value increases when the parameter (θ= 5) and the decision variables are basic، with the except of X24, X34.Whenever the parameter value increase, the objectiv
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Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)
It is well known that the spread of cancer or tumor growth increases in polluted environments. In this paper, the dynamic behavior of the cancer model in the polluted environment is studied taking into consideration the delay in clearance of the environment from their contamination. The set of differential equations that simulates this epidemic model is formulated. The existence, uniqueness, and the bound of the solution are discussed. The local and global stability conditions of disease-free and endemic equilibrium points are investigated. The occurrence of the Hopf bifurcation around the endemic equilibrium point is proved. The stability and direction of the periodic dynamics are studied. Finally, the paper is ended with a numerical simul
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Cervical Uterine Cancer is a disease that explains the vulnerability in which women are in terms of reproductive health with an impact on occupational health and public health, even when in Mexico the prevalence rate is lower than the other member countries of the OECD, its impact on Human Development and Local Development shows the importance that the disease have in communities more than in cities where prevention policies through check-ups and medical examinations seem to curb the trend, but show the lack of opportunities and capacities of health centers in rural areas. To establish the reliability, validity, and correlations between the variables reported in the literature with respect to their weighting in a public hospital. A
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In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.
Introduction: Breast cancer is the most common cancer and the major cause of cancer related deaths among Iraqi women. Due to the relatively late detection of breast cancer, the majority of the patients are still treated by modified radicle mastectomy. Aim: To assess the time lag between diagnosis of breast cancer and mastectomy among Iraqi patients; correlating the findings with other clinicopathological characteristics of the disease. Patients and methods: This retrospective study enrolled 226 Iraqi female patients who were diagnosed with breast cancer. Data were registered on the exact time period between signing the histopathological report and the surgical treatment. Other recorded variables included the age of the patients, their level
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