Artificial Intelligence in Pediatrics
Abstract
Pediatrics is a specialty with significant promise for the application of artificial intelligence (AI) technologies, in part due to the richness of its datasets, with relatively more complete longitudinal records and often less heterogeneous patterns of disease compared to adult medicine. Despite considerable overlap with adult medicine, pediatrics presents a distinct set of clinical problems to solve. It is tempting to assume that AI tools developed for adults will easily translate to the pediatric population, where in reality this is unlikely to be the case. The challenges involved in the development of AI tools for healthcare are unfortunately exacerbated in pediatrics, and the implementation gap between how these systems are developed and the setting in which they will be deployed is a real challenge for the next decade. Robust evaluation through high quality clinical study design and clear reporting standards will be essential. This chapter reviews recent work to develop artificial intelligence solutions in pediatrics, including developments across cardiology, respiratory, gastroenterology, neonatology, genetics, endocrinology, ophthalmology, radiology, pediatric intensive care, and radiology specialties. We conclude that AI presents an exciting opportunity to transform aspects of pediatrics at a global scale, democratizing access to subspecialist diagnostic skills, improving quality and efficiency of care, enabling global access to healthcare through sensor-rich Internet-connected mobile devices, and enhancing imaging acquisition to reduce radiation while improving speed and quality. The ultimate challenge will be for pediatricians to find ways to deploy these novel technologies into clinical practice in a way that is safe, effective, and equitable and that ultimately improves outcomes for children.
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