An artificial intelligence model for electrocardiogram detection of occlusion myocardial infarction: a retrospective study to reduce false-positive cath lab activations
The AI model is superior to traditional STEMI criteria for detecting OMI and has the potential to reduce false-positive catheterization lab activations. It can be a useful decision-aid for catheterization lab activation.
Authors
- Benjamin Karfunkle (ORCID: https://orcid.org/0000-0003-0170-4539)
- Nils P. Johnson (ORCID: https://orcid.org/0000-0002-0897-2301)
- Benjamin L. Cooper (ORCID: https://orcid.org/0000-0001-8820-6828)
- Catherine J. Reynolds (ORCID: https://orcid.org/0000-0002-1371-653X)
- Carrie Bakunas
- Elena Genova (ORCID: https://orcid.org/0000-0002-6692-6573)
Institutions
- Memorial Hermann (US)
Publication Details
- Journal
- European Heart Journal - Digital Health
- Published
- 2025-12-02
- DOI
- https://doi.org/10.1093/ehjdh/ztaf138
- Primary Topic
- Acute Myocardial Infarction Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00