Correlating exhaled aerosol images to small airway obstructive diseases: A study with dynamic mode decomposition and machine learning.
Journal:
PloS one
Published Date:
Jan 1, 2019
Abstract
BACKGROUND: Exhaled aerosols from lungs have unique patterns, and their variation can be correlated to the underlying lung structure and associated abnormities. However, it is challenging to characterize such aerosol patterns and differentiate their difference because of their complexity. This challenge is even greater for small airway diseases, where the disturbance signals are weak.