Machine Learning in Pediatric Healthcare: Current Trends, Challenges, and Future Directions.

ABSTRACT: Background/Objectives: Artificial intelligence (AI) and machine learning (ML) are transforming healthcare by enabling predictive, diagnostic, and therapeutic advancements. Pediatric healthcare presents unique challenges, including limited data availability, developmental variability, and ethical considerations. This narrative review explores the current trends, applications, challenges, and future directions of ML in pediatric healthcare. Methods: A systematic search of the PubMed database was conducted using the query: ("artificial intelligence" OR "machine learning") AND ("pediatric" OR "paediatric"). Studies were reviewed to identify key themes, methodologies, applications, and challenges. Gaps in the research and ethical considerations were also analyzed to propose future

SUBMITTER: Ganatra HA 

PROVIDER: S-EPMC11818243 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature