AI learns to predict colon cancer invasion from 5,000 videos
NCT ID NCT07401264
First seen Feb 16, 2026 · Last updated Jun 23, 2026 · Updated 23 times
Summary
This study collects images and videos of large colon polyps from 5,000 people undergoing colonoscopy. The goal is to train an artificial intelligence system to automatically predict whether a polyp has invaded deeper layers of the bowel wall. No drugs or treatments are tested—only data is gathered for future AI development.
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This is a summary of
the original study
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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.
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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Contacts and locations
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Study contacts
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Contact
Phone: •••-•••-•••• Email: •••••@•••••
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Contact
Phone: •••-•••-•••• Email: •••••@•••••
Locations
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UZ Leuven
RECRUITINGLeuven, 3000, Belgium
Contact Phone: •••-•••-•••• Email: •••••@•••••
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 an AI tool that helps doctors better predict which colon polyps are dangerous, potentially reducing unnecessary surgeries.
What could go wrong
This is an early-stage data collection study, not a treatment trial. The AI may not perform well enough in real-world settings, and results may take years to develop.
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.