Nathaniel Watson, MD, MSc1 • Cathy Goldstein, MD2 • Sam Rusk, BS3 • Chris R. Fernandez, MS3
Artificial intelligence (AI) combines clinical, environmental and laboratory based measures to allow a deeper understanding of sleep and sleep disorders. This article addresses various components and methods deployed in AI and covers examples of how AI is used to screen, endotype, diagnose, and treat sleep disorders. We then place this in the context of precision/personalized sleep medicine. We discuss pitfalls to ensure clinical AI implementation proceeds in the safest and most effective manner possible.
1 Department of Neurology, University of Washington School of Medicine, 2 Department of Neurology, University of Michigan School of Medicine, 3 EnsoData Research, 2 Santa Barbara Actuaries,