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Acute Myocardial Infarction Prediction Using Artificial Intelligence Applied to Electrocardiogram Images

NCT07163767 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 150000

Last updated 2025-12-18

No results posted yet for this study

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?

Conditions

  • Acute Myocardial Infarction (AMI)
  • Electrocardiography
  • Artifical Intelligence

Interventions

OTHER

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

Sponsors & Collaborators

  • Guangdong Provincial People's Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-08-01
Primary Completion
2028-12-31
Completion
2028-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07163767 on ClinicalTrials.gov