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Machine Learning Techniques for Analyzing Survival Data of Breast Cancer Patients in Baghdad
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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 component algorithm, The second kernel principal component algorithm, and The last is the faster ICA algorithm. Then the important features extracted in the three algorithms for features extraction will be entered into machine learning algorithms: The first K nearest neighbor algorithm, The second survival tree algorithm (or regression tree), and the last random survival forests algorithm.

Two criteria for comparing the best models to estimate survival have relied on the MSE and the C-Index. The best model for estimating and predicting survival is the use of the fastest ICA algorithm with the random survival forest algorithm that gave the lowest amount to MSE and the highest value to the C-Index. Accordingly, we recommend doctors and medical professionals in Iraq adopt this model to estimate survival for patients with breast cancer.

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Biochemical Action of Vaccines in Iraqi Patients with COVID-19 Infection
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      The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc :  COVID-19 patients ( without vaccine ) , Gp1: COVID-19 patients took one dose of Pfizer Biontech, Gp2 : COVID-19 patients took two doses of Pfizer Biontech, Ga1 : patients took one dose of AstraZeneca Oxford vaccine , Ga2: patients took two doses of AstraZeneca Oxford vaccine , Gs1 : patients took one dose of Sinopharm vaccine and Gs2:

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Publication Date
Thu Feb 01 2024
Journal Name
Indonesian Journal Of Chemistry
Synthesis, Characterization, and Evaluation of MCF-7 (Breast Cancer) for Schiff, Mannich Bases, and Their Complexes
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A new synthesis of Schiff (K) 6 and Mannich bases (Q) 7 had formed compound (Q) 7 by reacting compound (K) with N-methylaniline at the presence of formalin 35% to given Mannich base (Q). Additionally, new complexes were formed by reacting Schiff base (K) with metal salts CuCl2·2H2O, PdCl2·2H2O, and PtCl6·6H2O by 2:1 of M:L ratio. New ligands and their complexes were characterized, exanimated, and confirmed through several techniques, including FTIR, UV-visible, 1H-NMR, 13C-NMR spectroscopy, CHN analysis, FAA, TG, molar conductivity, and magnetic susceptibility. These compounds and their complexes were screened against breast cancer cells. It was determined that several of these compounds had a significant anti-breast cancer effec

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Publication Date
Sat Apr 19 2025
Journal Name
Journal Of Engineering
Image Compression Using 3-D Two-Level Techniques
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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Analyzing impact of competitive dimensions on the efficiency of e-learning: دراسه استطلاعيه
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The aim of this research is to diagnose the impact of competitive dimensions represented by quality, cost, time, flexibility on the efficiency of e-learning, The research adopted the descriptive analytical method by identifying the impact of these dimensions on the efficiency of e-learning, as well as the use of the statistical method for the purpose of eliciting results. The research concluded that there is an impact of the competitive dimensions on the efficiency of e-learning, as it has been proven that the special models for each of the research hypotheses are statistically significant and at a level of significance of 5%, and that each of these dimensions has a positive impact on the dependent variable, and the research recommended

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
3-D Packing in Container using Teaching Learning Based Optimization Algorithm
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The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Determination of Optimal Time-Average Wind Speed Data in the Southern Part of Malaysia
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Mersing is one of the places that have the potential for wind power development in Malaysia. Researchers often suggest it as an ideal place for generating electricity from wind power. However, before a location is chosen, several factors need to be considered. By analyzing the location ahead of time, resource waste can be avoided and maximum profitability to various parties can be realized. For this study, the focus is to identify the distribution of the wind speed of Mersing and to determine the optimal average of wind speed. This study is critical because the wind speed data for any region has its distribution. It changes daily and by season. Moreover, no determination has been made regarding selecting the average wind speed used for w

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Publication Date
Tue Jun 30 2009
Journal Name
Al-kindy College Medical Journal
Non-Metastatic Breast Cancer : Clinical Presentation and Patterns of Surgical Treatment
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Background : Breast cancer is the most common cancer of
women. When breast cancer is detected and treated early,
the chances for survival are better. Surgery is the most
important treatment for non-metastatic breast cancer.
Al-Kindy Col Med J 2008 Vol.5(1) 40 Original Article
Objectives : The aim of this study is to review different
clinical presentation and to evaluate types of surgical
procedures and complications in treatment of nonmetastatic breast cancer.
Method : During the period from Jun 1998 to May 2005,
93 patients with non-metastatic breast cancer were
diagnosed and treated surgically in 2 hospitals in Baghdad (
Hammad Shihab military hospital and Al-Kindy teaching
hospital).
Results : Wo

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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Enhancing the human resources quality by adopting an adventure learning method in their development
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The research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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