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).
The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
... Show MoreSome experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.
This cross-sectional, questionnaire-based study evaluated the knowledge, attitude and practice towards breast cancer and breast self-examination [BSE] among 387 [302 females and 85 males] educated Iraqis affiliated to 2 Iraqi universities. The participants were categorized into 3 occupations: student [71.3%], teaching staff [10.3%] and administrative staff [18.3%]. About half of the participants had a low knowledge score [< 50%]; only 14.3% were graded as [Good] and above. Almost 75% of the participants believed that the best way to control breast cancer was through early detection and other possible preventive measures. Most participants [90.9%] had heard of BSE, the main source of informatio
... Show MoreThe main purpose of the research is to diagnose the importance of the role that strategic memory plays with its three variables (content, structure, and processes) in helping the human resource department to use the COSO model with its five components (culture and governance, strategy and objectives, performance, communications and information, and feedback) in auditing activities and tasks Her own. As the research problem emphasized the existence of a lack of cognitive perception, of the importance of strategic memory, and the investment of its components in the rationalization of the application of the COSO model. and therefore it can be emphasized that the importance of the research is to provide treatments for problems relate
... Show MoreIdentifying 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
... Show MoreThe purpose behind building the linear regression model is to describe the real linear relation between any explanatory variable in the model and the dependent one, on the basis of the fact that the dependent variable is a linear function of the explanatory variables and one can use it for prediction and control. This purpose does not cometrue without getting significant, stable and reasonable estimatros for the parameters of the model, specifically regression-coefficients. The researcher found that "RUF" the criterian that he had suggested accurate and sufficient to accomplish that purpose when multicollinearity exists provided that the adequate model that satisfies the standard assumpitions of the error-term can be assigned. It
... Show MoreToday, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate
... Show MoreSemi-parametric regression models have been studied in a variety of applications and scientific fields due to their high flexibility in dealing with data that has problems, as they are characterized by the ease of interpretation of the parameter part while retaining the flexibility of the non-parametric part. The response variable or explanatory variables can have outliers, and the OLS approach have the sensitivity to outliers. To address this issue, robust (resistance) methods were used, which are less sensitive in the presence of outlier values in the data. This study aims to estimate the partial regression model using the robust estimation method with the wavel
... Show MoreThe current study was conducted in the period extending from November 2018 to October 2019 and designed as a case-control study and aimed to assess the seroprevalence of HCMV. However, a total number of 91serum specimens were collected to fulfill this purpose from females (71 breast cancer patients, and control group of 20 females) attending Al-Amal hospital for cancer management and Baghdad teaching hospital and the practical part was performed in College of Science, University of Baghdad. The study protocol was approved by the Ethics Committee at the Department of Biology (Reference: BEC/0220/0011). The immunological part for evaluation of seroprevalence of HCMV was accomplished by ELISA technique which revealed that anti-HCMV IgG was sco
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