AI breakthrough could spot hidden heart attacks in patients with tricky ECG patterns
NCT ID NCT07620119
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study is testing whether a computer program (machine learning) can help doctors diagnose severe heart attacks in patients who have a heart condition called left bundle branch block (LBBB). LBBB can hide the usual signs of a heart attack on an ECG, making it hard to tell if an artery is blocked. The AI will analyze ECG signals to find tiny patterns that humans might miss, and its results will be checked against the gold-standard test (angiography). The goal is to see if this tool can reduce unnecessary invasive procedures while catching real heart attacks faster.
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This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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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
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Locations
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Konya City Hospital
RECRUITINGKonya, Karatay, 42100, Turkey (Türkiye)
Contact Phone: •••-•••-•••• Email: •••••@•••••