Positional sleep apnea phenotyping using machine learning and digital oximetry biomarkers.

Yuval Ben SasonJeremy LevyArie OksenbergJonathan Aryeh SobelJoachim A Behar

Published in: Physiological measurement (2023)

Using OBMs computed in PP and NPP with OSA, it is possible to distinguish between the different phenotypes of POSA. This data-driven algorithm may be embedded in portable home sleep tests.

Keyphrases

sleep apnea
positive airway pressure
obstructive sleep apnea
machine learning
high throughput
deep learning
healthcare
sleep quality
physical activity
diffusion weighted imaging
low cost
neural network
magnetic resonance imaging
depressive symptoms
single cell
magnetic resonance