Deep learning electrocardiogram model for risk stratification of coronary revascularization need in the emergency department
The model was able to detect revascularization and type 1 MI with competitive performance, suggesting a potential role to complement current clinical assessment.
Authors
- Lars Eckardt (ORCID: https://orcid.org/0000-0002-3735-8503)
- Philipp Kümpers (ORCID: https://orcid.org/0000-0001-9929-0703)
- Philipp Neuhaus (ORCID: https://orcid.org/0000-0003-1028-2884)
- Julian Varghese (ORCID: https://orcid.org/0000-0002-7206-3719)
- Tobias Brix (ORCID: https://orcid.org/0000-0002-1557-8097)
- Dominik Heider (ORCID: https://orcid.org/0000-0002-3108-8311)
- Lucas Plagwitz (ORCID: https://orcid.org/0000-0001-7626-8853)
- Antonius Büscher (ORCID: https://orcid.org/0000-0003-1774-4252)
- Hermann Pavenstädt
- Lucas Bickmann (ORCID: https://orcid.org/0000-0001-9043-7844)
- Amélie Friederike Menke
- Kemal Yildirim (ORCID: https://orcid.org/0009-0009-2129-0952)
- Vincent F van Almsick
Institutions
- University of Münster (DE)
- University Hospital Münster (DE)
Publication Details
- Journal
- European Heart Journal
- Published
- 2025-03-29
- DOI
- https://doi.org/10.1093/eurheartj/ehaf254
- Citations
- 8
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 11.11