COPD Patients’ Readmission Using Machine Learning

Abstract

Patient reading can be considered an important factor in reducing costs while maintaining quality patient care. Therefore, predicting and managing patients effectively will lead to better outcomes. we are aiming to predict some of the readings of chronic obstructive pulmonary disease patients using some machine learning algorithms. By using Area under curve and accuracy are important features for calculating the predictive power of a model over any time period. Then clearly define the significance of the change for each value and then distinguish the significance of the change. study achieves the highest accuracy in estimating readings, with an ACC of 91%.