Application Evaluation Research on the Artificial Intelligence-assisted Support System for the Diagnosis of Colorectal Tubular Adenoma Lesions
This study is a prospective,multi-center and observational clinical study.Investigators would like to innovatively construct a trinity database of colorectal tubular adenomas based on white light - magnifying chromo - pathological images.It simulates the decision - making logic of doctors, and based on the multimodal endoscopic LAFEQ method previously proposed, develop a multimodal deep - learning diagnostic model for colon adenomas and an interpretable risk prediction model for intestinal adenomas. While achieving high - precision auxiliary treatment decisions, clearly present the decision - making basis, and break through the limitation of poor interpretability of previous medical imaging AI models.
• Patients aged ≥ 18 years, who need to undergo colonoscopy, regardless of gender.
• Voluntarily sign the informed consent form
• Promise to abide by the research procedures and cooperate in the implementation of the entire research process.