C-11: Human and Artificial Intelligence to Maximize Sleep Data (On-Demand Access Until 4/30/2025)

This course will provide an approach for seamless integration of human and artificial intelligence approaches to clinical sleep data. Computation and morphological analytic approaches will be presented to demonstrate how to extract the maximum possible clinically useful information from home sleep apnea testing, classic sleep laboratory testing, actigraphy, and selected consumer sleep tracking devices.

Upon completion of this activity, participants should be able to:

• Extract clinically useful information from EEG spectrograms;
• Recognize the varied patterns of respiratory control instability;
• Use actigraphy not just for simple sleep-wake estimation of circadian rhythms, but the quality of sleep and sleep fragmentation; and
• Gain confidence in the use of computational and morphological endotyping to provide Precision Sleep Care; and
• Evaluate complex patterns on the standard multicomponent sleep hypnogram.

Course Chair: Robert Thomas, MD

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Members: SLEEP2024M
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