Michael L. Seavers

A machine learning model for predicting six-month rehospitalization in heart failure patients with multiple comorbidities

A model is developed that classifies HF patients' readmission risk at discharge by evaluating approximately 20 parameters across five categories, including comorbidities, patient demographics, clinical data, and medication history, which aims to reduce readmissions and improve HF patient outcomes.