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.
This research abstract addresses various components and methods deployed in AI and covers examples of how AI is used to screen, endotype, diagnose, and treat sleep disorders.
In today’s post, we will be diving back into the future relationship of AI and sleep medicine, and how machine learning will lead to new opportunities in sleep.
By simplifying the process for analyzing the human body to accurately diagnose health conditions, we were thrilled to announce on June 10th the close of our $9 million Series A financing round.
The study examines a machine learning system, called NEXT, which provides a unique platform for real-world, reproducible active learning research. This paper details the challenges of building the system and demonstrates its capabilities with several experiments.