Department of Gastroenterology and Hepatology, University of Missouri-Kansas City School of Medicine, 5000 Holmes Street, Kansas City, MO, 64110, USA.
Division of Health Services and Outcomes Research, Children's Mercy Kansas City, Kansas City, MO, USA.
Dig Dis Sci. 2021 Jan;66(1):29-40. doi: 10.1007/s10620-020-06156-y. Epub 2020 Feb 27.
In line with the current trajectory of healthcare reform, significant emphasis has been placed on improving the utilization of data collected during a clinical encounter. Although the structured fields of electronic health records have provided a convenient foundation on which to begin such efforts, it was well understood that a substantial portion of relevant information is confined in the free-text narratives documenting care. Unfortunately, extracting meaningful information from such narratives is a non-trivial task, traditionally requiring significant manual effort. Today, computational approaches from a field known as Natural Language Processing (NLP) are poised to make a transformational impact in the analysis and utilization of these documents across healthcare practice and research, particularly in procedure-heavy sub-disciplines such as gastroenterology (GI). As such, this manuscript provides a clinically focused review of NLP systems in GI practice. It begins with a detailed synopsis around the state of NLP techniques, presenting state-of-the-art methods and typical use cases in both clinical settings and across other domains. Next, it will present a robust literature review around current applications of NLP within four prominent areas of gastroenterology including endoscopy, inflammatory bowel disease, pancreaticobiliary, and liver diseases. Finally, it concludes with a discussion of open problems and future opportunities of this technology in the field of gastroenterology and health care as a whole.
与当前医疗改革的轨迹一致,人们非常重视提高临床就诊过程中收集的数据的利用。虽然电子健康记录的结构化字段为开始此类工作提供了一个方便的基础,但人们清楚地知道,大量相关信息都局限在记录护理的自由文本叙述中。不幸的是,从这些叙述中提取有意义的信息是一项非平凡的任务,传统上需要大量的人工努力。如今,来自自然语言处理 (NLP) 领域的计算方法有望在医疗保健实践和研究中对这些文档的分析和利用产生变革性的影响,特别是在胃肠病学 (GI) 等以程序为主的子学科中。因此,本文提供了一个专注于胃肠病学实践中的 NLP 系统的临床综述。它首先详细概述了 NLP 技术的现状,介绍了临床环境和其他领域的最新方法和典型用例。接下来,它将围绕 NLP 在四个主要的胃肠病学领域(包括内窥镜、炎症性肠病、胰胆和肝脏疾病)中的当前应用进行全面的文献综述。最后,它将讨论该技术在胃肠病学领域和整个医疗保健领域的开放性问题和未来机遇。