National Cost Savings From Use of Artificial Intelligence Guided Echocardiography in the Assessment of Intermediate-Risk Patients With Syncope in the Emergency Department
If adopted widely, an AI-based TTE-first strategy applied to eligible ED patients presenting with syncope could yield substantial benefits by averting avoidable comprehensive TTE studies and saving bed hours.
Authors
- D. Baymon
- David A. Meguerdichian
- Yonatan G. Keschner (ORCID: https://orcid.org/0000-0003-3120-4666)
- Nicole M. Duggan (ORCID: https://orcid.org/0000-0003-4829-4979)
- Arun Nagdev (ORCID: https://orcid.org/0000-0002-7905-2350)
- Stephen Caplan (ORCID: https://orcid.org/0009-0008-2226-3721)
- Andrew Luo (ORCID: https://orcid.org/0000-0002-8367-7185)
- Andrew Goldsmith (ORCID: https://orcid.org/0000-0003-0979-7178)
- Christopher W. Baugh (ORCID: https://orcid.org/0000-0002-2360-1891)
- Tina Kapur (ORCID: https://orcid.org/0000-0003-3646-9508)
Institutions
- Brigham and Women's Hospital (US)
- Lahey Hospital and Medical Center (US)
- Harvard University (US)
- Alameda Health System (US)
- Massachusetts General Hospital (US)
- Lahey Medical Center (US)
Publication Details
- Journal
- Journal of the American College of Emergency Physicians Open
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1016/j.acepjo.2025.100139
- Citations
- 3
- Primary Topic
- Cardiovascular Syncope and Autonomic Disorders
- Type
- article
- Field-Weighted Citation Impact
- 6.02