Pediatric Artificial Intelligence in Radiology: Unmet Needs and Next Steps— AJR Expert Panel Review
Expert Panel Narrative Review examines the current landscape of pediatric AI in radiology and proposes practical priorities to support its safe and equitable adoption. The panel gives key recommendations, emphasizing the importance of an implementation roadmap to establish a dedicated pediatric AI infrastructure and standards that are essential to ensure diagnostic accuracy, workflow efficiency, and optimal clinical outcomes for children while minimizing bias and protecting patient safety.
Authors
- Jeannie K. Kwon (ORCID: https://orcid.org/0000-0002-2085-6573)
- Andy Tsai (ORCID: https://orcid.org/0000-0002-0089-6463)
- Marla B. K. Sammer (ORCID: https://orcid.org/0000-0002-0026-0326)
- Mario Sinti-Ycochea (ORCID: https://orcid.org/0000-0003-0656-3552)
- Hansel Otero
- Susan Sotardi
- Gary R. Schooler
Institutions
- Boston Children's Hospital (US)
- Children's Hospital of Philadelphia (US)
- Baylor College of Medicine (US)
- Southwestern Medical Center (US)
- Cigna (United States) (US)
- Texas Children's Hospital (US)
- Southwestern Medical Center (US)
- The University of Texas Southwestern Medical Center (US)
Publication Details
- Journal
- American Journal of Roentgenology
- Published
- 2026-09-09
- DOI
- https://doi.org/10.2214/ajr.26.35523
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00