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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 Jan 30 2020
Journal Name
Al-kindy College Medical Journal
Comparison between the Patterns of Common Breast Diseases Presenting as Breast Lumps in Pregnant and Non-Pregnant Married Women
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Background: Breast lump is one of the most common prevalent complaint of patients attending breast clinics.

Objective: To determine if there is any change in the pattern of common breast, diseases presenting as breast lumps between pregnant and non-pregnant women among patients attending Al-Elwiya Breast Clinic.

Methods: This is a cross – sectional study, with convent's patient sampling setting in AL-Elwiya Breast Cancer Early Detection Clinic from 1st Feb. to 1st May 2018, we collected data from patients with breast lumps including the age groups, pregnancy status, parity status, previous breast diseases, hormonal drugs, menstrual cycle, breast fe

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Publication Date
Sat Jan 01 2022
Journal Name
Food Science And Technology
Analyzing food production risk with Monte Carlo simulation
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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
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
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Fri Apr 12 2024
Journal Name
Revista Latinoamericana De Hipertension
Most common risk factors distribution for cervical cancer
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Publication Date
Wed Oct 21 2020
Journal Name
British Journal Of Cancer
Epigenome-wide analysis reveals functional modulators of drug sensitivity and post-treatment survival in chronic lymphocytic leukaemia
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Abstract<sec> <title>Background

Chronic lymphocytic leukaemia (CLL) patients display a highly variable clinical course, with progressive acquisition of drug resistance. We sought to identify aberrant epigenetic traits that are enriched following exposure to treatment that could impact patient response to therapy.

Methods

Epigenome-wide analysis of DNA methylation was performed for 20 patients at two timepoints during treatment. The prognostic significance of differentially methylated regions (DMRs) was assessed in independent cohorts of 139 and 1

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Publication Date
Thu Jan 06 2022
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Nurse-Midwife's Knowledge and Performance Regarding Immediate Newborn Care in Delivery Rooms at Maternity Hospitals in Baghdad City
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Objectives: To assess nurses-midwives knowledge and performance regarding immediate newborn care in delivery rooms, and to identify the relationship between nurses-midwives knowledge and performance and their socio-demographic and professional variables regarding immediate newborn care.

 

 

 

Methodology: A descriptive study was conducted from 1st of October, 2019 to 20TH of October, 2020 at three maternity teaching hospitals in Baghdad city/Al-Russafa Health Directorate: Al-Elwiya Maternity Teaching Hospital, Fatema Al- Zahra Maternity and Pediatric Hospital, Al- Za'faraniyah General Hospital. Non-probability (purposive sample) include

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Publication Date
Sat Jun 03 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn: 2789-3219 )
Analyzing the Potential Antioxidative Effects of Omega-369 in Preventing Acetaminophen-Induced Liver Damage
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Background: As acetaminophen (APAP) toxicity has become more common in many countries, related cases of poisoning, whether deliberate or unintentional, have been identified as a key contributor to acute liver failure. Aime: To discover if omega-369 fatty acids could protect the liver of male mice from the effects of acetamiophen. Methods: Thirty-five albino male mice were allocated to one of five groups at random. Group 1 served as the "negative control" and received a single intraperitoneal injection (10 ml/kg) of normal saline on the eleventh day of the test following ten days of receiving liquid paraffin orally at a dose of 10 ml/kg. The liquid paraffin was given to group 2 "positive control". Group 3 received Omega 369 (50 mg/kg

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of the Dominions of Mindfulness on the Organizational Innovation “Descriptive analytical study in some faculties of the University of Baghdad”
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Research seeks to test the impact of the dimensions of mindfulness on  organizational Innovation, proposed in the light of the review literature on two variables of the research, which referred in General to the dynamic relationship between them, as result of weakness of mindfulness as one important factor driving the diversity of innovation and time, ways to sustain and preserve and then support innovations made by creators, weakness in the overall level of organizational Innovation, this represents the problem research, data collection over designing   identification, distributed to sample Formed from (30) head Department at a number of colleges of the University of Baghdad, results confirms the validity of resea

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