人工智能与 IBD:我们现在在哪里,未来会在哪里?

Q1 Medicine Current Gastroenterology Reports Pub Date : 2024-05-01 Epub Date: 2024-02-27 DOI:10.1007/s11894-024-00918-8
Mehwish Ahmed, Molly L Stone, Ryan W Stidham
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引用次数: 0

摘要

审查目的:人工智能(AI)正迅速显示出解决 IBD 护理问题和挑战的能力。这篇带评论的综述将重点介绍当今人工智能在IBD图像分析、理解文本以及复制临床知识和经验方面的应用进展:机器学习方法的进步、高性能计算的可用性以及医疗数据的日益数字化,都为人工智能提供了协助 IBD 治疗的机会。多个研究小组已经证明了人工智能复制专家内镜评分的能力,并扩展到自动胶囊内镜检查、肠造影术和组织学解释。此外,人工智能图像分析还被用于开发新的内窥镜评分方法,其颗粒度和细节都比传统方法要高。事实证明,自然语言处理技术的进步减少了 IBD 护理过程中所需的繁重工作,包括文档记录、信息搜索和病历审查。最后,能够理解语言并生成类人回复的大型语言模型和聊天机器人开始展现临床智能,这将彻底改变我们提供 IBD 护理的方式。如今,人工智能正被用于复制专家在特定任务中的判断,在这些任务中,分歧、主观性和偏见很常见。然而,在不久的将来,人工智能将为我们所做不到的事情做出贡献,包括对 IBD 进行新的详细测量、增强图像分析,甚至可能实现护理的完全自动化。当我们推测未来的技术能力可能会改善我们对 IBD 的护理时,本综述也将考虑我们将如何在实践中实施和公平地使用人工智能。
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Artificial Intelligence and IBD: Where are We Now and Where Will We Be in the Future?

Purpose of review: Artificial intelligence (AI) is quickly demonstrating the ability to address problems and challenges in the care of IBD. This review with commentary will highlight today's advancements in AI applications for IBD in image analysis, understanding text, and replicating clinical knowledge and experience.

Recent findings: Advancements in machine learning methods, availability of high-performance computing, and increasing digitization of medical data are providing opportunities for AI to assist in IBD care. Multiple groups have demonstrated the ability of AI to replicate expert endoscopic scoring in IBD, with expansion into automated capsule endoscopy, enterography, and histologic interpretations. Further, AI image analysis is being used to develop new endoscopic scoring with more granularity and detail than is possible using conventional methods. Advancements in natural language processing are proving to reduce laborious tasks required in the care of IBD, including documentation, information searches, and chart review. Finally, large language models and chatbots that can understand language and generate human-like replies are beginning to exhibit clinical intelligence that will revolutionize how we deliver IBD care. Today, AI is being deployed to replicate expert judgement in specific tasks where disagreement, subjectivity, and bias are common. However, the near future will herald contributions of AI doing what we cannot, including new detailed measures of IBD, enhanced analysis of images, and perhaps even fully automating care. As we speculate on future technologic capabilities that may improve how we care for IBD, this review will also consider how we will implement and fairly use AI in practice.

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来源期刊
Current Gastroenterology Reports
Current Gastroenterology Reports Medicine-Gastroenterology
CiteScore
7.80
自引率
0.00%
发文量
19
期刊介绍: As the field of gastroenterology and hepatology rapidly evolves, the wealth of published literature can be overwhelming. The aim of the journal is to help readers stay abreast of such advances by offering authoritative, systematic reviews by leading experts. We accomplish this aim by appointing Section Editors who invite international experts to contribute review articles that highlight recent developments and important papers published in the past year. Major topics in gastroenterology are covered, including pediatric gastroenterology, neuromuscular disorders, infections, nutrition, and inflammatory bowel disease. These reviews provide clear, insightful summaries of expert perspectives relevant to clinical practice. An Editorial Board of internationally diverse members suggests topics of special interest to their country/region and ensures that topics are current and include emerging research. We also provide commentaries from well-known figures in the field.
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