Artificial intelligence in pediatric cardiology: taking baby steps in the big world of data

Artificial intelligence (AI) has changed virtually every aspect of modern life, and medicine is no exception. Pediatric cardiology is both a perceptual and a cognitive subspecialty that involves complex decision-making, so AI is a particularly attractive tool for this medical discipline. This review summarizes the foundational work and incremental progress made as AI applications have emerged in pediatric cardiology since 2020.

AI-based algorithms can be useful for pediatric cardiology in many areas, including: (1) clinical examination and diagnosis, (2) image processing, (3) planning and management of cardiac interventions, (4) prognosis and risk stratification, (5) omics and precision medicine, and (6) fetal cardiology. Most AI initiatives showcased in medical journals seem to work well in silico, but progress toward implementation in actual clinical practice has been more limited. Several barriers to implementation are identified, some encountered throughout medicine generally, and others specific to pediatric cardiology.

Despite barriers to acceptance in clinical practice, AI is already establishing a durable role in pediatric cardiology. Its potential remains great, but to fully realize its benefits, substantial investment to develop and refine AI for pediatric cardiology applications will be necessary to overcome the challenges of implementation.