AI could make heart attack risk detection safer and smarter

NCT ID NCT04193475

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study aims to improve how doctors interpret stress echocardiograms—ultrasounds of the heart during exercise—by using machine learning. Researchers will analyze data from 1,250 patients to develop more accurate tools for detecting blocked arteries and heart attack risk. The goal is to reduce the need for invasive follow-up tests and help doctors choose the best treatment for each patient.

What this could mean

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

What this could lead to

If successful, this could make stress echocardiograms more accurate, helping doctors identify heart disease risk earlier and reducing the need for invasive procedures.

What could go wrong

This is an observational study developing new analysis methods, not testing a treatment. The machine learning tools may not prove reliable enough for routine clinical use.

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.

Angina Pectoris cardiovascular disorder Chest Pain coronary artery disorder myocardial ischemia Sprains and Strains

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: •••••@•••••

Locations

  • Castle Hill Hospital

    RECRUITING

    Cottingham, HU165JQ, United Kingdom

    Contact Email: •••••@•••••