ABSTRACT Artificial intelligence (AI) is increasingly being used in healthcare and has the potential to improve the diagnosis, treatment, monitoring, and management of neurodevelopmental disorders (NDDs) in children. Early identification and personalized care are often constrained by subjective assessment and inequitable access. AI tools may enhance diagnostic accuracy and care delivery; however, the maturity, clinical readiness, and equity implications of this evidence base remain unclear. This scoping review mapped peer‐reviewed studies published in English since 2015 that described empirical or conceptual AI applications for diagnosis, monitoring, decision support, or treatment in pediatric NDD care, with particular attention to equity considerations. From 1027 records, 13 studies met the inclusion criteria. Most focused on attention deficit/hyperactivity disorder (ADHD, n = 7), autism spectrum disorder (ASD, n = 4), with predominating diagnostic tools. Reported accuracies ranged from 76% to 100% for ADHD and from 88% to 95% for ASD. Most studies were preliminary or in early implementations, with only one externally validated. Equity considerations were limited, with overrepresentation of White males and little attention paid to socioeconomic or cultural factors. AI shows promise for pediatric NDD care, but equitable clinical adoption will require inclusive research, external validation, and equity‐focused implementation.
Uzoaru et al. (Mon,) studied this question.