Algorithm aims to take guesswork out of colonoscopy scheduling
NCT ID NCT07658716
First seen Jun 23, 2026 · Last updated Jun 23, 2026
Summary
This study tests whether a computer algorithm can help doctors give more accurate recommendations for when patients should have their next colonoscopy. Researchers will compare the algorithm's suggestions to traditional methods, looking at both accuracy and the time it takes to make a decision. The study involves 100 gastroenterologists and primary care doctors from two hospitals.
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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: •••••@•••••
Locations
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NYU Langone Health
RECRUITINGNew York, New York, 10016, United States
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
colonoscopy surveillance recommendations algorithm
What this could lead to
If successful, this algorithm could help doctors make more accurate and faster decisions about when patients need a follow-up colonoscopy, potentially improving care and saving healthcare costs.
What could go wrong
This is a small, early-stage study with only 100 participants, all from two hospitals, so results may not apply broadly. The algorithm may not improve accuracy or efficiency in real-world practice.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.