Correlating exhaled aerosol images to small airway obstructive diseases: A study with dynamic mode decomposition and machine learning

Abstract

Considering that disease progression is inherently a dynamic process, DMD(C)-based feature extraction preserves temporal information and is preferred over POD and PCA. Compared with hand-crafted features like fractals, feature extraction by DMD and DMDC is automatic and more accurate.