An approach to reduce Readmission Rates
The objective for this project was to develop a model to reduce the readmission rate. The primary focus is to reduce the readmission rate of diabetic patients. We were provided with a dataset(10kdiabetes.csv) containing 52 features of patient records. We used the given dataset and applied chi-square analysis and built classification models based on machine learning algorithms to predict the most essential factors influencing the patient re-admission rate. Additionally, we proposed and analyzed other tasks that can strengthen the readmission risk model.