Predictive Modeling of Patient Readmission Risk using Machine Learning in Healthcare

Abstract

This research paper proposes a novel predictive modeling approach utilizing machine learning algorithms to assess the risk of patient readmission in healthcare settings. By leveraging electronic health records (EHR) data, including patient demographics, medical history, and clinical notes, our model demonstrates superior accuracy in identifying individuals at high risk of readmission. Implementation of this model can enable healthcare providers to allocate resources more effectively, enhance patient care management, and ultimately reduce healthcare costs.