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Colorectal cancer, as one of the most common malignant tumors of the digestive system, has a high incidence and mortality rate worldwide. High-quality colonoscopy is essential for the early detection and prevention of colorectal cancer and is key to improving the survival rates of patients. However, traditional colonoscopy faces numerous challenges in bowel preparation, such as inadequate preparation and a lack of personalized cleansing approaches. Therefore, it is particularly important to develop timely and efficient individualized bowel preparation methods. Artificial intelligence, especially deep learning technologies, has shown great potential in the medical field. This study aims to leverage the advantages of artificial intelligence to optimize the bowel preparation process before colonoscopy, creating a personalized bowel preparation plan that effectively improves the efficacy of colorectal cancer screening and diagnosis.
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Individuals who use smartphones.
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513 participants in 2 patient groups
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Central trial contact
Jianning Yao
Data sourced from clinicaltrials.gov
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