Diaper photos may spot hidden liver disease in babies

NCT ID NCT07697872

First seen Jul 13, 2026 · Last updated Jul 14, 2026 · Updated 1 time

Summary

This study explores whether a computer program can learn to spot signs of cholestasis—a liver condition where bile flow is blocked—by analyzing photos of dirty diapers taken by parents. Researchers will collect images from thousands of infants, both healthy and those with suspected liver issues, to see if the algorithm can accurately tell the difference. If it works, this simple, non-invasive approach could lead to earlier diagnosis and better outcomes for babies with serious liver diseases like biliary atresia.

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 algorithm analyzing parent-provided stool images
What this could lead to
If successful, this could enable early, non-invasive screening for liver conditions in newborns, potentially preventing long-term damage through timely treatment.
What could go wrong
The algorithm may not be accurate enough in real-world settings, and the study is observational, so it does not test treatment outcomes. Parent participation and image quality could also affect results.

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Conditions

The condition(s) this trial relates to.

As listed by the trial registrant

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

Contacts and locations

Locations

  • Birmingham Women's and Children's NHS Foundation Trust

    RECRUITING

    Birmingham, United Kingdom

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

    Contact

    Contact Email: •••••@•••••

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