Expert consensus on the application of colon cancer staging recognition system based on artificial intelligence platform (2021 edition)

Title: Expert consensus on the application of colon cancer staging recognition system based on artificial intelligence platform (2021 edition)
Edition: Original
Classification: Experts consensus
Field: Comprehensive guideline
Countries and regions: China
Guidelines users: Colorectal surgeons and people in the field of artificial intelligence
Evidence classification method: Grade A recommendation: Good scientific evidence suggests that the benefits of this medical practice substantially outweigh the potential risks. The clinician should discuss the medical practice with the applicable patient; Grade B recommendation: at least moderate evidence suggests that the benefits of the medical practice outweigh the potential risks. The clinician should discuss the medical behavior with the appropriate patient; Grade C recommendation: At least reasonable scientific evidence suggests that the medical practice provides benefits, but the benefits are too close to the risks to make a general recommendation. The clinician is not required to provide this medical practice unless there are some individual considerations; Grade D recommendation: at least reasonable scientific evidence suggests that the potential risks of the medical practice outweigh the potential benefits; Clinicians should not routinely perform this medical practice on asymptomatic patients; Level I recommendation: The medical practice lacks scientific evidence, or the evidence is of poor quality, or is conflicting, such as risks and benefits that cannot be measured and assessed. The clinician should help the patient understand the uncertainty of the medical practice.
Development unit: 中华医学会外科学分会结直肠外科学组;北京航空航天大学虚拟现实技术与系统国家重点实验室
Registration time: 2020-11-16
Registration number: IPGRP-2020CN180
Purpose of the guideline: At present, preoperative assessment of colon cancer stage mainly relies on imaging examination, and the results of imaging reading will directly determine the treatment of colon cancer patients. In order to alleviate the reading pressure of the radiologist, at the same time, further improve the efficiency and accuracy of imaging diagnosis, Colorectal Surgery Group of the Surgery Branch in the Chinese Medical Association joint Beihang University is proposed using artificial intelligence automatic identification system of auxiliary colon cancer staging imaging evaluation, so as to realize the automation and intelligence of image reading. The purpose of this consensus is to standardize the establishment, deep learning and verification process of artificial intelligence automatic identification system and guide its application in the staging, diagnosis and treatment of colon cancer.