AI-Powered 1-Minute ECG could spot hidden heart risks

NCT ID NCT07396792

First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study will enroll 5000 adults to see if a one-minute, single-lead ECG, analyzed by machine learning, can detect heart conditions like high blood pressure, heart failure, and diabetes. Participants will have their ECG recorded twice and compared with full medical exams. The goal is to find ECG patterns that reliably indicate disease, potentially enabling faster, cheaper screening.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance

single-channel electrocardiogram (ECG) with machine learning analysis

What this could lead to

If successful, this could lead to a quick, low-cost screening tool to detect heart disease and related conditions using just a simple ECG.

What could go wrong

This is an early observational study, not a treatment trial. The AI model may not be accurate enough for real-world use, and results may not apply to people with pacemakers or tremors.

Disclaimer Read more

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.

abdominal obesity-metabolic syndrome anemia Arrhythmias, Cardiac cardiac rhythm disease chronic kidney disease chronic renal failure syndrome coronary artery disorder diabetes mellitus essential hypertension heart failure heart valve disorder Hypercholesterolemia hypertensive disorder metabolic syndrome X ventricular arrhythmias due to cardiac ryanodine receptor calcium release deficiency syndrome

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Contacts and locations

Study contacts

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••