Machine learning for electrocardiogram (ECG) diagnosis and risk stratification of occlusion myocardial infarction
Study context
- Population
- Consecutive patients with chest pain at multiple clinical sites; Occlusion myocardial infarction (OMI) without ST-elevation on presenting ECG
- Participants
- 7,313 consecutive patients
- Exposure
- ML model for ECG diagnosis of OMI vs practicing clinicians and commercial interpretation systems
- Outcome
- ECG diagnosis of OMI
Methodological detailsmulticentre, external validation
- Multicentre
- External validation
Main finding
As reported in the abstract
OMI risk score combined with clinical judgment correctly reclassified one in three patients with chest pain
1 in 3
Observational data: associations, not effects.
Original publication
Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction. Nat Med. Published 29 June 2023. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →