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人工智能与炎症性肠病:我们将走向何方?

Artificial intelligence and inflammatory bowel disease: Where are we going?

机构信息

Department of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.

Department of Biomedical Sciences, Humanitas University, Rozzano 20089, Milano, Italy.

出版信息

World J Gastroenterol. 2023 Jan 21;29(3):508-520. doi: 10.3748/wjg.v29.i3.508.

Abstract

Inflammatory bowel diseases, namely ulcerative colitis and Crohn's disease, are chronic and relapsing conditions that pose a growing burden on healthcare systems worldwide. Because of their complex and partly unknown etiology and pathogenesis, the management of ulcerative colitis and Crohn's disease can prove challenging not only from a clinical point of view but also for resource optimization. Artificial intelligence, an umbrella term that encompasses any cognitive function developed by machines for learning or problem solving, and its subsets machine learning and deep learning are becoming ever more essential tools with a plethora of applications in most medical specialties. In this regard gastroenterology is no exception, and due to the importance of endoscopy and imaging numerous clinical studies have been gradually highlighting the relevant role that artificial intelligence has in inflammatory bowel diseases as well. The aim of this review was to summarize the most recent evidence on the use of artificial intelligence in inflammatory bowel diseases in various contexts such as diagnosis, follow-up, treatment, prognosis, cancer surveillance, data collection, and analysis. Moreover, insights into the potential further developments in this field and their effects on future clinical practice were discussed.

摘要

炎症性肠病,即溃疡性结肠炎和克罗恩病,是一种慢性且易复发的疾病,给全球的医疗系统带来了越来越大的负担。由于其病因和发病机制复杂且部分未知,溃疡性结肠炎和克罗恩病的治疗不仅在临床方面具有挑战性,而且在资源优化方面也是如此。人工智能是一个涵盖了机器为学习或解决问题而开发的任何认知功能的术语,其子集机器学习和深度学习在大多数医学专业中都越来越成为必不可少的工具,具有大量的应用。在这方面,胃肠病学也不例外,由于内镜检查和影像学的重要性,许多临床研究逐渐强调了人工智能在炎症性肠病中的相关作用。本综述的目的是总结人工智能在炎症性肠病的各个方面(如诊断、随访、治疗、预后、癌症监测、数据收集和分析)中的最新应用证据。此外,还探讨了该领域的潜在进一步发展及其对未来临床实践的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf07/9850939/6081dec937e0/WJG-29-508-g001.jpg

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