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Machine Learning Algorithms for COPD Patients Readmission Prediction: A Data Analytics Approach
Faculty
Computer Science
Year:
2022
Type of Publication:
ZU Hosted
Pages:
15279 - 15287
Authors:
Khalied Mohamed Hosny
Staff Zu Site
Abstract In Staff Site
Journal:
IEEE Access IEEE
Volume:
10
Keywords :
Machine Learning Algorithms , COPD Patients Readmission
Abstract:
Patients’ readmission can be considered as a critical factor affecting cost reduction while maintaining a high-quality treatment of patients. Therefore, predicting and controlling patients’ readmission rates would significantly improve the healthcare service. In this study, we aim at predicting the readmission of COPD (Chronic Obstructive Pulmonary Disease) patients through the deployment of machine learning algorithms. Area Under Curve (AUC) and ACCuracy (ACC) were considered as the main criteria for evaluating models’ prediction power in each time frame. Then, the importance of the variables for each outcome was explicitly identified, and defined important variables have then been differentiated. Our study could achieve the highest accuracy in predicting readmission with %91 ACC.
Author Related Publications
Khalied Mohamed Hosny, "SEMANTIC REPRESENTATION OF MUSIC DATABASE USING NEW ONTOLOGY-BASED SYSTEM", Journal of Theoretical and Applied Information Technology, 2020
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Khalied Mohamed Hosny, "Building a New Semantic Social Network Using Semantic Web-Based Techniques", ِASPG, 2021
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Khalied Mohamed Hosny, "New Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework", IEEE, 2022
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Khalied Mohamed Hosny, "Fast computation of accurate Zernike moments", Springer, 2008
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Khalied Mohamed Hosny, "Accurate Computation of QPCET for Color Images in Different Coordinate Systems", SPIE, 2017
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Department Related Publications
Saber Mohamed, "Online Generation of Trajectories for Autonomous Vehicles using a Multi-Agent System", IEEE, 2014
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Saber Mohamed, "Parameters Adaptation in Differential Evolution", IEEE, 2012
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Eman samir hasan sayed, "Using Hybrid Dependency Identification with a Memetic Algorithm for Large Scale Optimization Problems", Springer Berlin Heidelberg, 2012
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Eman samir hasan sayed, "A Decomposition-based Algorithm for Dynamic Economic Dispatch Problems", IEEE, 2014
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Eman samir hasan sayed, "Decomposition-based evolutionary algorithm for large scale constrained problems", Elsevier Inc, 2014
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