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Erschienen in:
2021 | OriginalPaper | Buchkapitel
47. Diabetes Patients Hospital Re-admission Prediction Using Machine Learning Algorithms
verfasst von : Sneha Grampurohit
Erschienen in: Intelligent Manufacturing and Energy Sustainability
Verlag: Springer Singapore
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Abstract
The excess amount of blood glucose in the body leads to a chronic disease called diabetes. It causes severe damage to the eyes, kidneys, nerves, and other parts of body. Hospital re-admission is a scenario in which the patient gets re-admitted to the hospital after a certain duration of time. Diabetes patient’s hospital re-admission majorly impacts on the healthcare cost reduction as diabetic patients are more likely to get re-admitted than those without diabetes. The proposed work aims to predict the re-admission of diabetic patients and highlight the factors that lead to re-admission within 30 days of their discharge considering the database of 10-year administrative patients’ record using decision tree and AdaBoost classifiers. With all the preprocessing and feature selection techniques, the proposed approach has obtained an accuracy of 95%.