Artificial Intelligence in Pediatric Dentistry, A Systematic Review

Abstract

Pedodontics, or pediatric dentistry, encompasses the prevention, diagnosis, and management of dental conditions in children from infancy through adolescence. It requires a deep understanding of the developmental, psychological, and physiological aspects unique to younger patients.Artificial Intelligence (AI), a term introduced by John McCarthy in 1955, pertains to the capacity of machines to acquire knowledge and apply it to perform a range of cognitive tasks, such as language processing, reasoning, learning, and decision-making, essentially emulating human behavior. Machine Learning (ML), a term coined by Arthur Samuel in 1959, is a subset of AI that equips systems with the ability to autonomously learn and improve from experience without explicit programming. ML is instrumental in developing computer programs that can access data and autonomously learn from it. The incorporation of AI components into imaging machines can alleviate the workload and enhance efficiency. Pediatric dentistry benefits from various applications of artificial intelligence, and the  aim of this systematic review was to evaluate the effectiveness of AI as a diagnostic tool in pediatric dentistry.