Spadaccini Marco, Massimi Davide, Mori Yuichi, Alfarone Ludovico, Fugazza Alessandro, Maselli Roberta, Sharma Prateek, Facciorusso Antonio, Hassan Cesare, Repici Alessandro
Department of Biomedical Sciences, Humanitas University, 20090 Rozzano, Italy.
Endoscopy Unit, Humanitas Clinical and Research Center, IRCCS, 20090 Rozzano, Italy.
Diagnostics (Basel). 2023 Mar 14;13(6):1102. doi: 10.3390/diagnostics13061102.
Colorectal cancer (CRC) is the third most common cancer worldwide, with the highest incidence reported in high-income countries. However, because of the slow progression of neoplastic precursors, along with the opportunity for their endoscopic detection and resection, a well-designed endoscopic screening program is expected to strongly decrease colorectal cancer incidence and mortality. In this regard, quality of colonoscopy has been clearly related with the risk of post-colonoscopy colorectal cancer. Recently, the development of artificial intelligence (AI) applications in the medical field has been growing in interest. Through machine learning processes, and, more recently, deep learning, if a very high numbers of learning samples are available, AI systems may automatically extract specific features from endoscopic images/videos without human intervention, helping the endoscopists in different aspects of their daily practice. The aim of this review is to summarize the current knowledge on AI-aided endoscopy, and to outline its potential role in colorectal cancer prevention.
结直肠癌(CRC)是全球第三大常见癌症,在高收入国家报告的发病率最高。然而,由于肿瘤前体进展缓慢,以及存在内镜检测和切除的机会,精心设计的内镜筛查计划有望大幅降低结直肠癌的发病率和死亡率。在这方面,结肠镜检查的质量与结肠镜检查后结直肠癌的风险明显相关。最近,人工智能(AI)在医学领域的应用发展越来越受到关注。通过机器学习过程,以及最近的深度学习,如果有大量的学习样本,人工智能系统可以在无需人工干预的情况下自动从内镜图像/视频中提取特定特征,在日常实践的不同方面帮助内镜医师。本综述的目的是总结关于人工智能辅助内镜检查的当前知识,并概述其在结直肠癌预防中的潜在作用。