Chao Wei-Lun, Manickavasagan Hanisha, Krishna Somashekar G
Department of Computer Science, Cornell University, New York, NY 14853, USA.
Department of Computer Science and Engineering, Ohio State University, Columbus, OH 43210, USA.
Diagnostics (Basel). 2019 Aug 20;9(3):99. doi: 10.3390/diagnostics9030099.
Research in computer-aided diagnosis (CAD) and the application of artificial intelligence (AI) in the endoscopic evaluation of the gastrointestinal tract is novel. Since colonoscopy and detection of polyps can decrease the risk of colon cancer, it is recommended by multiple national and international societies. However, the procedure of colonoscopy is performed by humans where there are significant interoperator and interpatient variations, and hence, the risk of missing detection of adenomatous polyps. Early studies involving CAD and AI for the detection and differentiation of polyps show great promise. In this appraisal, we review existing scientific aspects of AI in CAD of colon polyps and discuss the pitfalls and future directions for advancing the science. This review addresses the technical intricacies in a manner that physicians can comprehend to promote a better understanding of this novel application.
计算机辅助诊断（CAD）研究以及人工智能（AI）在胃肠道内镜评估中的应用是新颖的。由于结肠镜检查和息肉检测可降低结肠癌风险，因此受到多个国家和国际协会的推荐。然而，结肠镜检查是由人工进行的，存在显著的操作者间和患者间差异，因此存在漏诊腺瘤性息肉的风险。早期涉及CAD和AI用于息肉检测与鉴别的研究显示出巨大潜力。在本评估中，我们回顾了AI在结肠息肉CAD中的现有科学方面，并讨论推进该科学的陷阱和未来方向。本综述以医生能够理解的方式阐述技术复杂性，以促进对这一新颖应用的更好理解。
