Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

Background. The presence of black triangles around the dental implant-supported prosthesis and the failure to construct adequate papillae around them bothers dental implantologists. Peri-implant surgical soft tissue management will improve esthetics, function, and implant survival. Aim. To compare the effects of rolled and nonrolled U-shaped flaps combined with a temporary crown in enhancing the soft tissue around dental implants. Materials and Methods. Forty patients were included in this study; all patients were operated on by the same maxillofacial surgeon at Al-Iraq specialized dental clinics from January 2019 to January 2020. Patients were divided randomly into two groups: group A: at the second stage of implant surgery, a U-sh

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

This paper compare  the accurecy of HF propagation  prediction programs for  HF circuits links between Iraq and  different points world wide  during August 2018 when  solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode  used. The prediction   programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 )  had been used to generat HF circuit link  parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending  on the predicted parameters (data)  , real radio contacts had been done using a radio transceiver from Icom  model IC 7100 with 100W RF

Background: Pemphigus vulgaris (PV) is an autoimmune vesiculobullous mucocutaneous disease with life-threatening consequences. Rituximab (RTX) has recently emerged as an effective treatment for PV. Objectives: This study aims to determine changes in neutrophil and platelet counts for PV patients treated with RTX or corticosteroids combined with Imuran (azathioprine). Materials and Methods: The present cross-sectional study was conducted in the Department of Dermatology at Baghdad Teaching Hospital, Baghdad, Iraq. Thirty PV patients received two types of treatment: 15 patients were administered RTX and 15 patients took corticosteroids with Imuran (azathioprine). Neutrophil and platelet counts were detected at the hospital laboratory. Results

     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written