Why the study?
Accurate echocardiographic assessment is critical for congenital heart disease, and artificial intelligence has the potential to reduce labor and automate assessment in pediatric cardiology.
Artificial intelligence and deep learning hold promise for automating and improving the accuracy of echocardiographic assessment in pediatric and fetal congenital heart disease.
May aid automated congenital heart disease assessment; leaves open prospective validation before clinical use.
Echocardiography is the primary tool in pediatric cardiology for diagnosing and managing congenital heart disease (CHD). Accurate and reliable echocardiographic assessment is critical in clinical decision making. Artificial intelligence (AI), in particular deep learning, has the potential to reduce labor and provide automated assessment of CHD. In this review, the application of AI in pediatric and fetal echocardiography are described with the need for future multicenter collaboration to fully leverage the use of AI for echocardiography in the pediatric population.
No takes yet. Share an insight, caveat, or question.
Gearhart et al. (2022) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: