TIEVis: a Visual Analytics Dashboard for Temporal Information Extracted from Clinical Reports

Robin De Croon, A. Leeuwenberg, J. Aerts, Marie-Francine Moens, Vero Vanden Abeele, K. Verbert
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引用次数: 1

Abstract

Clinical reports, as unstructured texts, contain important temporal information. However, it remains a challenge for natural language processing (NLP) models to accurately combine temporal cues into a single coherent temporal ordering of described events. In this paper, we present TIEVis, a visual analytics dashboard that visualizes event-timelines extracted from clinical reports. We present the findings of a pilot study in which healthcare professionals explored and used the dashboard to complete a set of tasks. Results highlight the importance of seeing events in their context, and the ability to manually verify and update critical events in a patient history, as a basis to increase user trust.
TIEVis:从临床报告中提取时间信息的可视化分析仪表板
临床报告作为非结构化文本,包含重要的时间信息。然而,对于自然语言处理(NLP)模型来说,将时间线索准确地组合成描述事件的单一连贯时间顺序仍然是一个挑战。在本文中,我们介绍了TIEVis,一个可视化分析仪表板,可以将从临床报告中提取的事件时间线可视化。我们介绍了一项试点研究的结果,在该研究中,医疗保健专业人员探索并使用仪表板完成了一组任务。结果强调了在其上下文中查看事件的重要性,以及手动验证和更新患者历史中的关键事件的能力,作为增加用户信任的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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