1. Binary Classification: Create a classification model that can accurately predict if a patient will be readmitted to the hospital within 30 days of being discharged. A robust prediction can enable healthcare providers to implement preventive measures and provide timely intervention, potentially saving millions of dollars in healthcare costs.
2. Multiclass Classification: The second objective is to develop a multiclass classifier that predicts the timeframe of a patient's readmission, with the classes being "No", "<30 days", ">30 days". This model can provide more nuanced insights into patient risk levels and help hospitals tailor their post-discharge care and follow-up procedures accordingly.