The 30-days hospital readmission risk in diabetic patients: predictive modeling with machine learning classifiers.

ABSTRACT:

Background and objectives

Diabetes mellitus is a major chronic disease that results in readmissions due to poor disease control. Here we established and compared machine learning (ML)-based readmission prediction methods to predict readmission risks of diabetic patients.

Methods

The dataset analyzed in this study was acquired from the Health Facts Database, which includes over 100,000 records of diabetic patients from 1999 to 2008. The basic data distribution characteristics of this dataset were summarized and then analyzed. In this study, 30-days readmission was defined as a readmission period of less than 30 days. After data preprocessing and normalization, multiple risk factors in the dataset were examined for classifier training to predict the probability of readmission

SUBMITTER: Shang Y 

PROVIDER: S-EPMC8323261 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature