Artificial Intelligence, ECG Pattern, Myocardial Infarction, Acute
Conditions
Keywords
myocardial infarction, artificial Intelligence, 12 lead electrocardiogram
Brief summary
the algorithm of artificial intelligent to diagnose myocardial infarction through prior surgery Electrocardiogram was established. The accuracy of using artificial intelligent to diagnose acute ST-segment elevation myocardial infarction and judge criminal vascular was evaluated.
Interventions
According to coronary angiogram results, the accuracy of STEMI patients' electrocardiogram diagnosis by artificial intelligence was evaluated.
Sponsors
Study design
Eligibility
Inclusion criteria
1. age≥18 years old; 2. the admitting doctor's diagnosis is ST-segment Elevation Myocardial Infarction.
Exclusion criteria
1. the admitting diagnosis is non-ST-segment Elevation Myocardial Infarction. 2. default data; 3. pregnancy, mental disorder, kidney failure; 4. except for criteria mention above, including some improper condition considered by investigators.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| the algorithm of artificial intelligent to diagnose myocardial infarction through prior surgery Electrocardiogram | 24 hours | All the electrocardiograms done before coronary arteriography were read by artificial intelligent. Then according to results of coronary angiogram, artificial intelligent can establish a algorithm of to diagnose myocardial infarction. |
| The accuracy of using artificial intelligent to diagnose acute ST-segment elevation myocardial infarction and judge criminal vascular | 24 hours | The accuracy of using artificial intelligent to diagnose acute ST-segment elevation myocardial infarction and judge criminal vascular was evaluated. |
Countries
China