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Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver operating characteristic ROC).   Dataset was downloaded from UCI ml repository; it is composed of 9 attributes and 699 samples. The findings are clearly showing that the RBF NN classifier is the best in prediction of the type of breast tumors since it had recorded the highest performance in terms of correct classification rate (accuracy), sensitivity, specificity, and AUC (area under Receiver Operating Characteristic ROC) among all other models.</p>

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Publication Date
Thu Feb 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
SUGGESTING MULTIPHASE REGRESSION MODEL ESTIMATION WITH SOME THRESHOLD POINT
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The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
"RUF procedures forgetting the best subset linear regression model"
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The 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

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Publication Date
Mon Mar 03 2025
Journal Name
Internationaljournalof Economicsandfinancestudies
CROSS-SECTIONAL REGRESSION WITH PROXIES: A SEMI-PARAMETRIC METHOD
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This study investigates asset returns within the Iraq Stock Exchange by employing both the Fama-MacBeth regression model and the Fama-French three-factor model. The research involves the estimation of cross-sectional regressions wherein model parameters are subject to temporal variation, and the independent variables function as proxies. The dataset comprises information from the first quarter of 2010 to the first quarter of 2024, encompassing 22 publicly listed companies across six industrial sectors. The study explores methodological advancements through the application of the Single Index Model (SIM) and Kernel Weighted Regression (KWR) in both time series and cross-sectional analyses. The SIM outperformed the K

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Publication Date
Sat Jan 02 2021
Journal Name
The International Journal Of Nonlinear Analysis And Application
Atan regularized for the high dimensional Poisson regression model
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Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

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Publication Date
Mon Mar 31 2025
Journal Name
Iraqi Statisticians Journal
Hypothesis Testing for Non-Normal Multiple Compact Regression Model
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Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Correlation Expression between P52 and BCL2 among Iraqi Women with Breast Carcinoma
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Publication Date
Sun Mar 13 2011
Journal Name
Baghdad Science Journal
The Effect of Silybum marianum L. aquatic crude extracts on the cancer cell lines and normal cell line in vitro
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The aquatic crude extract of Silybum marianum dry grains prepared by melting them in distil water by the method of soak and shake. The effect of Silybum marianum crude extract studied in vitro on three tumor cell line the Hep-2, AMN-3 and RD for 24, 48 and 72 hours of exposure, and one cell line of normal cells REF for 72 hr exposure. The results showed that the prescence of toxic effect of the aquatic crude extract on the cell lines of Hep-2, AMN-3 and RD at 10 and 100 µg/ ml upto the higher concentrations when they exposed to the extract for 48 hr. as compared with the control treatment, and when the exposure period increased to 72 hr. the toxic effect started at low concentrations (5 and 10 µg/ ml) as compared with the control g

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Green synthesis of nano binary oxide SiO2/V2O5 NPs integrated ointment cream application on wound dressings and skin cancer cells
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Green synthesis is depending on preparation of nano composited SiO2/V2O5 by using the modified sol-gel method depending on rice husk ash as a source for the extraction of silica gel and the product powder of nano composited SiO2/V2O5 characterization by many techniques such as X-ray diffraction spectroscopy (XRD), field emission scanning electron microscopy (FESEM), and N2 adsorptions/desorption isotherms (BET). This study also includs the biological effectiveness of SiO2/V2O5 and its effect on inhibiting bacterial growth after the prepared nanomaterial was applied to wound dressings, which gave a promising result for its use as

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Publication Date
Wed Nov 27 2024
Journal Name
Frontiers In Education
The impact of using artificial intelligence techniques in improving the quality of educational services/case study at the University of Baghdad
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The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.

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Publication Date
Wed Nov 27 2024
Journal Name
Frontiers In Education
The impact of using artificial intelligence techniques in improving the quality of educational services/case study at the University of Baghdad
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The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional

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