AI could spare thousands from unnecessary scans for gallstones

NCT ID NCT06066372

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

Summary

This study tests whether a machine learning model can accurately predict gallstones in the bile duct, potentially reducing the need for invasive endoscopic ultrasound or MRI. Researchers will enroll 1,000 adults with a moderate chance of having gallstones. If the model works well, it could help doctors decide who truly needs further testing.

What this could mean

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

Active substance

machine learning model

What this could lead to

If successful, this could help doctors avoid unnecessary invasive procedures like endoscopic ultrasound or MRI for many patients with suspected gallstones.

What could go wrong

This is an early-stage diagnostic study, not a treatment trial. The model may not be accurate enough in real-world settings, 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.

choledocholithiasis

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: •••••@•••••

Locations

  • Asian Institute of Gastroenterology

    RECRUITING

    Hyderabad, Telangana, 500032, India

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