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Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficacy of several classification algorithms on four reputable datasets, using both the full features set and the reduced features subset selected through the proposed method. The results show that the feature selection technique achieves outstanding classification accuracy, precision, and recall, with an impressive 97% accuracy when used with the Extra Tree classifier algorithm. The research reveals the promising potential of the feature selection method for improving classifier accuracy by focusing on the most informative features and simultaneously decreasing computational burden.

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Publication Date
Sun Jan 03 2016
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Complication Following percutaneous coronary intervention via the femoral artery Experience in lraqi center for the Heart Disease and lbn Al-Bitar Hospital for cardiac surgery.
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Background: Vascular complications have been recognized as an important factor in morbidity after diagnostic and percutaneous coronary interventions.
Objectives: This study sought to evaluate vascular complications after diagnostic coronary angiography and percutaneous coronary intervention (PCI) from the common femoral artery.
Patients and methods: This prospective cohort study was carried out over a year period, from February 2008 till January 2009, at the Iraqi Center for the Heart Disease and Ibn Al-Bitar Hospital for Cardiac Surgery. A total number of 2400 patients underwent 3600 procedures, diagnostic coronary angiography (2196) and PCI(1404) via their common femoral arteries were included in this study.
Result: A total 40

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Recording of an ECG, PCG, and PPG for Feature Extractions
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Recently, the development of the field of biomedical engineering has led to a renewed interest in detection of several events. In this paper a new approach used to detect specific parameter and relations between three biomedical signals that used in clinical diagnosis. These include the phonocardiography (PCG), electrocardiography (ECG) and photoplethysmography (PPG) or sometimes it called the carotid pulse related to the position of electrode.

Comparisons between three cases (two normal cases and one abnormal case) are used to indicate the delay that may occurred due to the deficiency of the cardiac muscle or valve in an abnormal case.

The results shown that S1 and S2, first and second sound of the

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
A Study on the Accuracy of Prediction in Recommendation System Based on Similarity Measures
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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Study the Factors Effecting on Welding Joint of Dissimilar Metals
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The aim of this work is to study the factors that affect the welding joint of dissimilar metals. Austenitic stainless steel-type AISI (316L) with a thickness of (2mm) was welded to carbon steel (1mm) using an MIG spot welding.  The filler metal is a welding wire of the type E80S-G (according to AWS) is used with (1.2mm) diameter and CO2 is used as shielding gas with flow rate (7L/min) for all times was used in this work.

        The results indicate that the increase of the welding current tends to increase the size of spot weld, and also increases the sheer force.  Whereas the sheer force increased inversely with the time of welding. Furthermore, the results indicate that i

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Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The Role Of The economic And External Factors In Selecting Aggregate Planning Alternatives For Workforce Case Study In Yarmouk Teaching Hospital
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The research aimed to achieve many objectives represented in two variables, which are the impacted factors and the aggregate planning alternatives of workforce in Educational Al- yarmouk Hospital , This research started from a problem focused on finding solutions to the demand’s  fluctuation  or the energy limitation while the study importance is emerged from diagnosis the suitable strategy and adopt the suitable alternatives due to their importance in meeting the demand for the health service submitted by the hospital .This study  based on choosing assumptions of connection relationship and the impact among the mentioned variables in the(surgery and internal diseases) departments. The research is dependent on ch

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Factors associated with nonalcoholic fatty liver disease grades detected by ultrasound at a screening center in Klang Valley, Malaysia.
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Background: Non-alcoholic fatty liver disease (NAFLD) is a very common liver disease in the world, particularly in Western and developed countries. It is rapidly growing in the Asia- Pacific region.
Objectives: This study was designed to determine the association between risk factors and non-alcoholic fatty liver disease grades among Malaysian adults.
Patients and Methods: A cross-sectional observational study design was prospectively carried out in this study. Consecutive 628 respondents who attended for a medical checkup at urban health center had been recruited for the study. All respondents had the physical examination, blood tests, clinical assessments, and abdominal ultrasoun

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Publication Date
Fri Jan 13 2023
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Effect of Dapagliflozin on hemoglobin level in heart failure patients with chronic kidney disease and/or diabetes
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Background: Heart failure is a complex clinical syndrome caused by any functional or structural cardiac disease that reduces the ventricle's ability to fill or pump blood. Anemia is frequent in patient with heart failure and is associated with deterioration through the activation of neuro-hormonal pathways. Dapagliflozin is a selective and reversible inhibitor of Sodium-glucose co-transporter-2 (SGLT2). Dapagliflozin increases hemoglobin level through different mechanisms such increasing plasma concentration by diuresis or increasing Erythropoietin synthesis.

Objective: To evaluate the effect of additional dapagliflozin into conventional therapy on hemoglobin in heart failure patients with chronic

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Publication Date
Fri May 17 2019
Journal Name
Lecture Notes In Networks And Systems
Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Applying Ensemble Classifier, K-Nearest Neighbor and Decision Tree for Predicting Oral Reading Rate Levels
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For many years, reading rate as word correct per minute (WCPM) has been investigated by many researchers as an indicator of learners’ level of oral reading speed, accuracy, and comprehension. The aim of the study is to predict the levels of WCPM using three machine learning algorithms which are Ensemble Classifier (EC), Decision Tree (DT), and K- Nearest Neighbor (KNN). The data of this study were collected from 100 Kurdish EFL students in the 2nd-year, English language department, at the University of Duhok in 2021. The outcomes showed that the ensemble classifier (EC) obtained the highest accuracy of testing results with a value of 94%. Also, EC recorded the highest precision, recall, and F1 scores with values of 0.92 for

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Predicting Social Security Fund compensation in Iraq using ARMAX Model
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Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ

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