AI on a simple ECG: a new way to gauge heart attack severity?
NCT ID NCT07751809
First seen Aug 07, 2026 · Last updated Aug 07, 2026
Summary
This study tests whether artificial intelligence can read a standard ECG to predict how much heart muscle is damaged after a heart attack. Researchers will compare AI-ECG results with MRI images, the current gold standard, in 461 patients who had a heart attack and underwent a procedure to open blocked arteries. The goal is to see if the AI can identify large areas of damage, poor pumping function, or blocked microvessels, potentially offering a faster and more accessible assessment.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
- Active substance
- Artificial intelligence-enhanced electrocardiography (AI-ECG) algorithms (AiTiA LVSD and AiTiA MI)
- What this could lead to
- If successful, this could lead to a quick, widely available ECG-based tool to assess heart attack severity and guide treatment without needing an MRI.
- What could go wrong
- This is a retrospective validation study, so it may not reflect real-world performance. The AI algorithms might not be accurate enough to replace MRI, and results may not generalize to other populations.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
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Yongin Severance Hospital, Yonsei University College of Medicine
Yongin-si, Gyeonggi-do, 16995, South Korea
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