Applications of artificial intelligence in early childhood health management: a systematic review from fetal to pediatric periods

Abstract

AI holds transformative potential across the pediatric continuum of care-from fetal screening to chronic disease management. However, most applications remain in the research phase, constrained by data heterogeneity, lack of prospective validation, and insufficient regulatory alignment. To advance clinical adoption, future efforts should focus on multicenter collaboration, standardized data sharing frameworks, explainable AI, and pediatric-specific regulatory pathways. This review provides a roadmap for clinicians, researchers, and policymakers to guide the responsible translation of AI in child health.

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