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消化内镜领域的人工智能——我们现在所处的位置以及未来的发展方向?

Artificial Intelligence in Digestive Endoscopy-Where Are We and Where Are We Going?

作者信息

Vulpoi Radu-Alexandru, Luca Mihaela, Ciobanu Adrian, Olteanu Andrei, Barboi Oana-Bogdana, Drug Vasile Liviu

机构信息

Institute of Gastroenterology and Hepatology, Saint Spiridon Hospital, "Grigore T. Popa" University of Medicine and Pharmacy, 700111 Iași, Romania.

Institute of Computer Science, Romanian Academy-Iași Branch, 700481 Iași, Romania.

出版信息

Diagnostics (Basel). 2022 Apr 8;12(4):927. doi: 10.3390/diagnostics12040927.

Abstract

Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly becoming part of the endoscopy lab. It has developed considerably since the first attempt at developing an automated medical diagnostic tool, today being adopted in almost all medical fields, digestive endoscopy included. The detection rate of preneoplastic lesions (i.e., polyps) during colonoscopy may be increased with artificial intelligence assistance. It has also proven useful in detecting signs of ulcerative colitis activity. In upper digestive endoscopy, deep learning models may prove to be useful in the diagnosis and management of upper digestive tract diseases, such as gastroesophageal reflux disease, Barrett's esophagus, and gastric cancer. As is the case with all new medical devices, there are challenges in the implementation in daily medical practice. The regulatory, economic, organizational culture, and language barriers between humans and machines are a few of them. Even so, many devices have been approved for use by their respective regulators. Future studies are currently striving to develop deep learning models that can replicate a growing amount of human brain activity. In conclusion, artificial intelligence may become an indispensable tool in digestive endoscopy.

摘要

人工智能是一种基于计算机的概念,试图模拟人类思维,它正逐渐成为内镜检查实验室的一部分。自从首次尝试开发自动化医疗诊断工具以来,它已经有了很大的发展,如今几乎被应用于所有医学领域,包括消化内镜检查。在人工智能的辅助下,结肠镜检查期间癌前病变(即息肉)的检出率可能会提高。它在检测溃疡性结肠炎活动迹象方面也已被证明是有用的。在上消化道内镜检查中,深度学习模型可能在诊断和管理上消化道疾病(如胃食管反流病、巴雷特食管和胃癌)方面有用。与所有新的医疗设备一样,在日常医疗实践中的应用存在挑战。监管、经济、组织文化以及人与机器之间的语言障碍就是其中的一些挑战。即便如此,许多设备已获得各自监管机构的使用批准。目前,未来的研究正在努力开发能够复制越来越多人类大脑活动的深度学习模型。总之,人工智能可能会成为消化内镜检查中不可或缺的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cef/9029251/cfcbeb786ba9/diagnostics-12-00927-g001.jpg

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