Short-Term and Long-Term Readmission Prediction in Uncontrolled Diabetic Patients using Machine Learning Techniques

Monira Mahmoud, Mohamed Bader, James McNicholas, James McNicholas

2023

Abstract

Diabetes is a chronic disease and major health problem which leads to many complications if not managed probably. Hyperglycemia, or raised blood sugar, is a common effect of Uncontrolled diabetes that may leads overtime to serious complications, especially in the nerves and blood vessels. As well as leads to repeated hospital admission. The main purpose of this study is to help clinicians to improve healthcare of uncontrolled diabetic patients through using machine learning as a tool in decision making, consequently this will improve patient care and reduce the readmission which considered a medical quality measurement and cost reduction objective. This study aims to predict the hospital readmission of the uncontrolled diabetic patient who is considered more susceptible to developing life-threatening diabetes complications and based on the Diabetes 130-US hospitals dataset. Several machine learning employed to predict the short term (within 30 days), and both short and long-term readmission (within or after 30 days) of uncontrolled diabetic patient. As expected, the results are in line with other research in the literature. For the first scenario of whole readmission prediction, our model achieved a better accuracy of 64.5 % with SVM and attribute selection and for the second scenario, RF achieved the highest accuracy of 86.38 % which still come in context with other research in the literature.

Paper Citation

in Harvard Style

Mahmoud M., Bader M. and McNicholas J. (2023). Short-Term and Long-Term Readmission Prediction in Uncontrolled Diabetic Patients using Machine Learning Techniques. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: CCH, ISBN 978-989-758-631-6, pages 680-688. DOI: 10.5220/0011926000003414

in Bibtex Style

@conference{cch23,
author={Monira Mahmoud and Mohamed Bader and James McNicholas},
title={Short-Term and Long-Term Readmission Prediction in Uncontrolled Diabetic Patients using Machine Learning Techniques},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: CCH,},
year={2023},
pages={680-688},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011926000003414},
isbn={978-989-758-631-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: CCH,
TI - Short-Term and Long-Term Readmission Prediction in Uncontrolled Diabetic Patients using Machine Learning Techniques
SN - 978-989-758-631-6
AU - Mahmoud M.
AU - Bader M.
AU - McNicholas J.
PY - 2023
SP - 680
EP - 688
DO - 10.5220/0011926000003414