Machine Learning Algorithms for COPD Patients Readmission Prediction: A Data Analytics Approach

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 predi...

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Bibliographic Details
Published in:IEEE access 2022, Vol.10, p.15279-15287
Main Authors: Mohamed, Israa, Fouda, Mostafa M., Hosny, Khalid M.
Format: Article
Language:English
Subjects:
Algorithms
Chronic obstructive pulmonary disease
Classification algorithms
COPD readmission
Costs
data mining
Data models
decision support systems
healthcare data analytics
Hospitals
Machine learning
Medical services
Predictive control
Predictive models
Support vector machines
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Summary: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.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2022.3148600