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Acute Myocardial Infarction Prediction Using Artificial Intelligence Applied to Electrocardiogram Images
Sponsor: Guangdong Provincial People's Hospital
Summary
The goal of this observational study is to develop and validate an artificial intelligence(AI)-based prediction model for new-onset acute myocardial infarction(AMI) using electrocardiogram(ECG) data. The main question it aims to answer is whether the AI-based ECG accurately forecast new-onset AMI by previous ECG data with 'normal' diagnosis?
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
150000
Start Date
2025-08-01
Completion Date
2028-12-31
Last Updated
2025-12-18
Healthy Volunteers
Yes
Interventions
Deep learning approach of ECG for AMI detection
AMIdECG was trained to perform AMI detection in a supervised manner as a classification task. And the classification labels of AMI subtypes (" STEMI "or" NSTEMI ") or non-AMI states used during the training phase are real-world diagnostic results
Locations (1)
Guangdong Provincial People's Hospital
Guangzhou, Guangdong, China