Predicting PAP Adherence

Utilizing machine learning based on multi-modal data to predict PAP adherence in patients with OSA

This study highlights the use of machine learning based on multi-modal data to predict PAP adherence in patients with OSA, presented by Kaiser Permanente and EnsoData Research.

Deep Learning to Predict PAP Adherence in Obstructive Sleep Apnea

In this study, EnsoData shows how ML algorithms based on PAP usage can predict future adherence, offering potential for personalized treatment decisions and preemptive interventions when upcoming non-adherence is predicted.