Pediatric Sleep Medicine: Tailoring Artificial Intelligence Solutions for the Youngest Patients

Artificial intelligence (AI) is increasingly relevant to pediatric sleep medicine, a field defined by complex physiologic signals, longitudinal behavioral data, time-intensive expert scoring, and uneven access to subspecialty care. Because sleep physiology, respiratory control, symptom expression, and monitoring tolerance change across development, pediatric practice cannot rely on adult-derived algorithms without age-specific training and validation. This review highlights the current evidence for AI-assisted obstructive sleep apnea screening and severity estimation, automated sleep staging, and more informative analysis of actigraphy and wearable signals. These tools may help reduce burden, support home and longitudinal monitoring, and streamline human review.