Detettori echocardiografici automatizzati di malformazioni cardiache congenite utilizzando l'intelligenza artificiale.

BACKGROUND: Delayed or missed diagnosis of congenital heart disease (CHD) contributes to excess pediatric mortality worldwide. Echocardiography (echo) is central to diagnosing and triaging CHD, yet expert interpretation remains a scarce and maldistributed global resource. Artificial intelligence offers the potential to democratize diagnostics and to extend expert-level interpretation beyond large academic centers, but its application in CHD remains underexplored. METHODS: We developed EchoFocus-CHD, an artificial intelligence-enabled model for automated detection of 12 critical and 8 noncritical CHD lesions, individually and as composites. The composite critical CHD outcome was the primary