-Diabetes-Machine-learning-project-

Hospital readmission is a critical metric in healthcare, serving as a primary indicator of treatment efficacy and patient outcomes. High readmission rates, particularly within a 30-day window, often lead to severe financial penalties for hospitals under standard CMS (Centers for Medicare & Medicaid Services) guidelines.

This project implements a complete Machine Learning pipeline designed to predict hospital readmissions for diabetic patients. Using a comprehensive healthcare dataset of over 100,000 records, the system processes raw clinical data, mitigates class imbalance, and trains robust classification models to identify high-risk patients.