Comparison of machine learning algorithms for the identification of acute exacerbations in chronic obstructive pulmonary disease

Identifying acute exacerbations in chronic obstructive pulmonary disease (AECOPDs) is of utmost importance for reducing the associated mortality and financial burden. In this research, the authors aimed to develop identification models for AECOPDs and to compare the relative performance of different modeling paradigms to find the best model for this task. Data were extracted from electronic medical records (EMRs) of patients with chronic...