No timestamps are available for this session due to the loosely structured nature of a discussion group.

Summary

Artificial intelligence (AI) has grown exponentially in the 21st century and promises to revolutionize the healthcare industry. Radiology and oncology have already begun pioneering this frontier by utilizing AI technologies to interpret radiographic images and use biomarkers to predict cancers.

While still in its infancy in sleep medicine, AI has the potential to transform diagnostic accuracy and efficiency, identify patients at risk for noncompliance with therapeutic interventions before initiation of therapy, and tailor personalized treatments for sleep disorders. From scoring to interpretation of raw data waveforms in polysomnograms, to identifying biomarkers and endotypes of sleep and sleep disorders, AI offers impactful, real-world applications for sleep medicine. Through real-time sleep health monitoring and large-scale data analysis of information gathered from consumer-based wearable devices, health records, and sleep surveys, AI offers insights into population-level sleep patterns, evolution of sleep disorders, and outcomes. Hence, AI is set to be a “total game-changer” in filling the gaps in knowledge in the practice of sleep medicine.