A deep learning algorithm was developed and validated for detecting moderate or greater aortic stenosis (AS) using AI-guided focused cardiac ultrasound (FoCUS), including prospective evaluation by novice operators across multiple Mayo Clinic sites (Midwest, Arizona, Florida) from 2005–2025.
The model achieved AUROC of 0.99 across all validation cohorts. In prospective novice-operator use (n=1302), 96.6% of exams were analyzable, with sensitivity 93% and specificity 96%; adding expert review of AI-positive and uninterpretable exams raised PPV from 49.4% to 91.1% (sensitivity 85.4%).
Single health system (Mayo Clinic), which may limit generalizability; novice operators still required expert review of flagged/uninterpretable cases to achieve acceptable PPV; PPV of 49.4% with AI alone reflects a relatively low prevalence of moderate+ AS in the screened population.
AI-guided FoCUS operated by novice users can reliably screen for moderate or greater AS — a hybrid model pairing AI triage with targeted expert review of positive and uninterpretable exams may expand access in resource-limited settings. Clinicians should note that AI-alone PPV (~49%) requires expert confirmation before acting on positive results.
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