Can artificial intelligence predict heart valve disease progression?

NCT ID NCT06749132

ENROLLING_BY_INVITATION Knowledge-focused Sponsor: Yale University Source: ClinicalTrials.gov ↗

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

Summary

This study will enroll 210 adults aged 65 and older with early aortic stenosis (a heart valve narrowing) to see if an artificial intelligence tool can better predict how fast the disease worsens. Participants will have standard echocardiograms, and researchers will compare the AI's risk score to actual changes over time. The goal is to improve personalized monitoring and timing of potential treatments.

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 lead to a more accurate way to monitor aortic stenosis progression, helping doctors decide when to intervene before symptoms worsen.

What could go wrong

This is an observational study, not a treatment trial. The AI tool may not prove reliable enough for widespread use, and results may not apply to all patient groups.

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.

aortic valve calcification aortic valve stenosis

As listed by the trial registrant

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

Contacts and locations

Locations

  • Icahn School of Medicine at Mount Sinai

    New York, New York, 10029, United States

  • The Methodist Hospital Research Institute

    Houston, Texas, 77030, United States

  • Yale New Haven Health System

    New Haven, Connecticut, 06519, United States