Prediction of Aortic Stenosis Progression Using Artificial Intelligence
Our novel, echocardiography-focused artificial intelligence model is a reliable tool for the early identification of patients at risk of progression to severe AS. Pending future, multicenter, prospective validation, such models may facilitate personalized follow-up strategies and timely interventions, ultimately leading to improved patient outcomes and resource utilization.
Authors
- Ran Kornowski (ORCID: https://orcid.org/0000-0002-7708-8253)
- Yuval Altman
- Edward Itelman (ORCID: https://orcid.org/0000-0003-0142-0253)
- Leor Perl (ORCID: https://orcid.org/0000-0002-0625-7937)
- Alon Shechter (ORCID: https://orcid.org/0000-0001-9670-4026)
- Yaron Shapira (ORCID: https://orcid.org/0000-0002-8464-6006)
- Nadav Loebl
Institutions
- Reichman University (IL)
- Rabin Medical Center (IL)
- Herzliya Medical Center (IL)
Publication Details
- Journal
- JACC Advances
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1016/j.jacadv.2025.102121
- Primary Topic
- Cardiac Valve Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00