Silverman Anna L, Shung Dennis, Stidham Ryan W, Kochhar Gursimran S, Iacucci Marietta
Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Scottsdale, Arizona.
Section of Digestive Diseases, Department of Medicine, Yale School of Medicine, Yale University, New Haven, Connecticut.
Clin Gastroenterol Hepatol. 2025 Feb;23(3):428-439.e4. doi: 10.1016/j.cgh.2024.05.048. Epub 2024 Jul 9.
Artificial intelligence (AI) refers to computer-based methodologies that use data to teach a computer to solve pre-defined tasks; these methods can be applied to identify patterns in large multi-modal data sources. AI applications in inflammatory bowel disease (IBD) includes predicting response to therapy, disease activity scoring of endoscopy, drug discovery, and identifying bowel damage in images. As a complex disease with entangled relationships between genomics, metabolomics, microbiome, and the environment, IBD stands to benefit greatly from methodologies that can handle this complexity. We describe current applications, critical challenges, and propose future directions of AI in IBD.
人工智能(AI)是指基于计算机的方法,这些方法利用数据来训练计算机解决预定义任务;这些方法可用于识别大型多模态数据源中的模式。人工智能在炎症性肠病(IBD)中的应用包括预测治疗反应、内镜检查的疾病活动评分、药物发现以及识别图像中的肠道损伤。作为一种在基因组学、代谢组学、微生物群和环境之间存在复杂关系的疾病,炎症性肠病将从能够处理这种复杂性的方法中受益匪浅。我们描述了人工智能在炎症性肠病中的当前应用、关键挑战,并提出了未来的发展方向。