Tsukanov Vladislav V, Vasyutin Alexander V, Kasparov Edward V, Tonkikh Julia L
Clinical Department of the Digestive System Pathology of Adults and Children, Federal Research Center "Krasnoyarsk Science Center" of the Siberian Branch of the Russian Academy of Sciences, Scientific Research Institute of Medical Problems of the North, Krasnoyarsk 660022, Russia.
World J Gastroenterol. 2025 Jun 14;31(22):106500. doi: 10.3748/wjg.v31.i22.106500.
Colorectal cancer (CRC) is the third most frequently diagnosed cancer and the second leading cause of cancer death worldwide. In this regard, CRC screening is one of the most important issues in modern preventive medicine. Colorectal polyps are potential predictors of CRC, and therefore represent one of the leading targets for screening colonoscopy. The difficulty of analyzing the information obtained during colonoscopy, including the size, location, shape, type of polyps, the need to standardize morphological data, determines that recently a number of works have promoted the opinion on the advisability of using various artificial intelligence (AI) methods to improve the effectiveness of endoscopic screening for CRC. At the same time, they point to a number of errors and methodological problems in the use of AI systems for the diagnosis of colorectal polyps. In this regard, the interpretation of the work of Shi , devoted to the use of a machine learning-based predictive model for monitoring the results of colorectal polypectomy, is undoubtedly interesting. In our opinion, the prospects for using AI to assess endoscopic screening for CRC look certainly positive, but the road to its widespread use will not be easy.
结直肠癌(CRC)是全球第三大常见诊断癌症,也是第二大致癌死亡原因。在这方面,CRC筛查是现代预防医学中最重要的问题之一。结直肠息肉是CRC的潜在预测指标,因此是结肠镜筛查的主要目标之一。分析结肠镜检查期间获得的信息存在困难,包括息肉的大小、位置、形状、类型,以及标准化形态学数据的必要性,这决定了最近一些研究提出了关于使用各种人工智能(AI)方法来提高CRC内镜筛查有效性的观点。同时,他们指出了在使用AI系统诊断结直肠息肉时存在的一些错误和方法问题。在这方面,Shi等人关于使用基于机器学习的预测模型监测结直肠息肉切除结果的研究解读无疑很有趣。我们认为,使用AI评估CRC内镜筛查的前景肯定是积极的,但广泛应用之路并不容易。