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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
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Demonstration of the value of diffusion weighted MR imaging for differentiation of benign from malignant breast lesions
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Background: Radiologic evaluation of breast lesions is being achieved through several imaging modalities. Mammography has an established role in breast cancer screening and diagnosis. Still however, it shows some limitations particulary in dense breast.

Methods : Magnetic resonance imaging is an attractive tool for the diagnosis of breast tumors1 and the use of magnetic resonance imaging of the breast is rapidly increasing as this technique becomes more widely available.1 As an adjunct to mammography and ultrasound, MRI can be a valuable addition to the work-up of a breast abnormality. MRI has the advantages of providing a three-dimensional view of the breast, performing wit

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Involvement of Total Antioxidant Activity and eNOS Gene rs1799983/ rs2070744 Polymorphisms in Breast Carcinogenesis
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Globally, breast cancer is the common malignancy affecting women and understanding its associated molecular events could help in disease prevention and management strategies. The present study was set to investigate an association between total antioxidant capacity (TAC) and endothelial nitric oxide synthase (eNOS) polymorphisms with breast cancer. For this purpose, 100 subjects were participated in this work, including 50 female patients diagnosed with breast cancer recruited from Oncology hospital, Baghdad - Iraq and 50 healthy women as a control group. The concentration of antioxidants was measured in the serums collected from blood samples of breast cancer patients and healthy controls. While eNOS SNPs (rs1799983, G894T and rs2070744, T

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Publication Date
Wed Jan 30 2013
Journal Name
Al-kindy College Medical Journal
Electrocardiographic changes among beta-thalassemic major patients in ibn al-baladi thalassemia center-Baghdad
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Background :Thalassemia is an autosomal
disease of the haemoglobin. Two types of
thalassemia are recognized: thalassemia major
and thalassemia intermedia.
The most serious cardiac complication in
thalassemia major is due to multiple blood
transfusions rather than the disease itself, which
is due to iron overload.
Cardiomyopathy is the most common cardiac
defect that occurs with iron overload. Pricarditis,
congestive heart failure and arrhythmias are due
to hemosidrosis and chronic aneamia.
Aim of the study: to demonstrate the prevalence
and types of electrocardiographic changes among
thalassemic patients with aged over ten years old.

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Publication Date
Sun Jan 01 2017
Journal Name
Research Journal Of Pharmacy And Technology
Estimating the plain and negative tendonography techniques for evaluating injured tendon in rabbit
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Publication Date
Wed May 10 2023
Journal Name
Journal Of Planner And Development
The impact of population density in sustainable housing - An applied study in the city of Baghdad (Mahalla 817), Al-Bayaa as a model
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Population density represents an important indicator for determining the growth of the size of urban areas. Population density has a direct impact on the quality of life, and its excessive rise may lead to the deterioration of basic service facilities. The problem of the research is that the increase in the total population densities of the residential neighborhood may reflect negatively on the nature of the services provided to the residents in these shops, and thus the failure to achieve sustainability in the residential locality. The research assumes that the increase in population densities negatively affects the achievement of sustainability in the residential neighborhood.

 

      

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Social Worked-Examples Technique to Enhance Student Engagement in Program Visualization
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Learning programming is among the top challenges in computer science education. A part of that, program visualization (PV) is used as a tool to overcome the high failure and drop-out rates in an introductory programming course. Nevertheless, there are rising concerns about the effectiveness of the existing PV tools following the mixed results derived from various studies. Student engagement is also considered a vital factor in building a successful PV, while it is also an important part of the learning process in general. Several techniques have been introduced to enhance PV engagement; however, student engagement with PV is still challenging. This paper employed three theories—constructivism, social constructivism and cognitive load t

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Wed Jun 28 2023
Journal Name
Internet Technology Letters,
The Blockchain for Healthcare 4.0 Apply in Standard Secure Medical Data Processing Architecture
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Cloud-based Electronic Health Records (EHRs) have seen a substantial increase in usage in recent years, especially for remote patient monitoring. Researchers are interested in investigating the use of Healthcare 4.0 in smart cities. This involves using Internet of Things (IoT) devices and cloud computing to remotely access medical processes. Healthcare 4.0 focuses on the systematic gathering, merging, transmission, sharing, and retention of medical information at regular intervals. Protecting the confidential and private information of patients presents several challenges in terms of thwarting illegal intrusion by hackers. Therefore, it is essential to prioritize the protection of patient medical data that is stored, accessed, and shared on

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Publication Date
Wed Jul 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Fast and robust approach for data security in communication channel using pascal matrix
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This paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
A Modified 2D-Checksum Error Detecting Method for Data Transmission in Noisy Media
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In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me

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