AI outperforms old methods in predicting Post-Surgery bowel issues
NCT ID NCT07267767
First seen Dec 12, 2025 · Last updated May 15, 2026 · Updated 14 times
Summary
This study looked at 3500 rectal cancer patients who had minimally invasive surgery to save their sphincter. Researchers tested seven different computer models, including six machine learning methods, to see which best predicts a condition called low anterior resection syndrome (LARS) — a set of bowel problems that can occur after surgery. The goal was to find the most accurate model to help doctors identify patients at higher risk.
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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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