An Explainable Artificial Intelligence Framework For Risk Prediction Of Copd In Smokers

This article discusses the use of machine learning algorithms to predict the stage of chronic obstructive pulmonary disease (COPD). It reviews existing research on the use of digital oximetry biomarkers, CT imaging, and variable selection methods to diagnose COPD. It also provides an overview of supervised machine learning algorithms such as random forest and principal component methods for imputing missing values.