AI could spare thousands from unnecessary scans for gallstones

NCT ID NCT06066372

Recruiting now Diagnosis Sponsor: Asian Institute of Gastroenterology, India Source: ClinicalTrials.gov ↗

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.

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.

choledocholithiasis

As listed by the trial registrant

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

CHOLEDOCHOLITHIASIS

Contacts and locations

Locations

Asian Institute of Gastroenterology
RECRUITING

Hyderabad, Telangana, 500032, India

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