Comparison of different Machine Learning Models for Predicting Chronic Obstructive Pulmonary Disorder Hospital Readmissions

Chronic Obstructive Pulmonary Disease (COPD) is a prevalent chronic pulmonary condition that affects hundreds of millions of people all over the world. Being progressive in nature, Chronic Obstructive Pulmonary Disease (COPD) patients require frequent hospital readmission. Readmission can be avoided if additional attention is paid to patients with high readmission risk. Machine learning (ML) based prediction models proved to be fast, accurate, and free from human errors with capabilities to address pressing problems in healthcare. In this research we compare the relative performance of different modeling paradigms to find the best model for this task.