OBJECTIVE
To evaluate whether a validated artificial intelligence-enabled electrocardiography (AI-ECG) model for left ventricular diastolic function (LVDF) can provide prognostic risk stratification in patients with significant mitral annulus calcification (MAC).
METHODS
We included patients who underwent transthorac...
G. Tsaban, E. Lee, Y. Wong et al.· Mayo Clinic proceedings· 0 citations
Real-time artificial intelligence (AI) guidance may enable imaging-naïve users to acquire images suitable for diagnosis using handheld focused cardiac ultrasound (FoCUS).
To compare image quality and diagnostic performance of novice-acquired FoCUS scans using two commercially available AI-guidance handheld...
M. Killalea, M. Gulati, J. Kovac et al.· European Heart Journal· 0 citations
In this retrospective cohort and using the current AI-ECG model, BAV detection showed modest diagnostic performance and limited standalone clinical utility, suggesting that ECG-only screening for BAV may require additional modalities or more refined phenotyping.
Manuel A. Montoya-Hernández, Francisco López-Jiménez, T. Poterucha et al.· Journal of the Heart Valve S...· 0 citations
A deep learning algorithm accurately detected moderate or greater AS across validation cohorts in this study and support a scalable strategy that may expand access to AS detection in settings with limited echocardiography resources.
Eunjung Lee, J. Naser, Conor J. Kane et al.· JAMA cardiology· 1 citation
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