Artificial intelligence (AI) has arrived and it will directly impact how we assess, monitor, and manage inflammatory bowel disease (IBD). Advances in the machine learning methodologies that power AI have produced astounding results for replicating expert judgment and predicting clinical outcomes, particularly in the analysis of imaging. This review will cover general concepts for AI in IBD, with descriptions of common machine learning methods, including decision trees and neural networks. Applications of AI in IBD will cover recent achievements in endoscopic image interpretation and scoring, new capabilities for cross-sectional image analysis, natural language processing for automated understanding of clinical text, and progress in AI-powered clinical decision support tools. In addition to detailing current evidence supporting the capabilities of AI for replicating expert clinical judgment, speculative commentary on how AI may advance concepts of disease activity assessment, care pathways, and pathophysiologic mechanisms of IBD will be addressed.

中文翻译：

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用于炎症性肠病疾病评估的人工智能：它将如何改变我们的实践？


人工智能 (AI) 已经到来，它将直接影响我们评估、监测和管理炎症性肠病 (IBD) 的方式。为人工智能提供动力的机器学习方法的进步在复制专家判断和预测临床结果方面产生了令人震惊的结果，特别是在成像分析方面。这篇综述将涵盖 IBD 中人工智能的一般概念，并描述常见的机器学习方法，包括决策树和神经网络。人工智能在 IBD 中的应用将涵盖内窥镜图像解读和评分方面的最新成就、横截面图像分析的新功能、用于自动理解临床文本的自然语言处理以及人工智能驱动的临床决策支持工具的进展。除了详细说明支持人工智能复制专家临床判断能力的现有证据外，还将讨论人工智能如何推进疾病活动评估、护理途径和 IBD 病理生理机制概念的推测性评论。