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.

Inclusion Criteria:

• Patients who underwent painless colonoscopy at the Digestive Endoscopy Center of the First Affiliated Hospital of Zhengzhou University and signed the informed consent for the clinical trial.

Individuals who use smartphones.

Exclusion Criteria:

• Patients with contraindications for colonoscopy. Individuals in whom successful cecal intubation could not be achieved.