AI spots silent heart condition in seconds

NCT ID NCT06469372

Completed Diagnosis Sponsor: Pierre Elias Source: ClinicalTrials.gov ↗

First seen Jun 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study tested a computer model that uses a patient's age, sex, medical history, and heart tests (ECG and echocardiogram) to estimate their risk of having cardiac amyloidosis, a serious but often undiagnosed heart condition. Researchers invited 50 high-risk patients for further testing to see if the model could find new cases. The goal is to see if this AI tool can help doctors catch the disease earlier than usual.

What this could mean

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

Active substance: deep learning model (device)
What this could lead to: If successful, this could lead to earlier detection of cardiac amyloidosis, a serious heart condition that is often missed.
What could go wrong: This is a small, single-center study with only 50 participants. The model may not work as well in other populations or settings.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

Amyloid Neuropathies, Familial amyloidosis

As listed by the trial registrant

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

CARDIAC AMYLOIDOSIS

Contacts and locations

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Locations

Columbia University Irving Medical Center / NewYork-Presbyterian Hospital

New York, New York, 10032, United States

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