Towards event sequence representation, reasoning and visualization for EHR data

C. Tao, K. Wongsuphasawat, Kimberly Clark, C. Plaisant, B. Shneiderman, C. Chute
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引用次数: 25

Abstract

Efficient analysis of event sequences and the ability to answer time-related, clinically important questions can accelerate clinical research in several areas such as causality assessments, decision support systems, and retrospective studies. The Clinical Narrative Temporal Reasoning Ontology (CNTRO)-based system is designed for semantically representing, annotating, and inferring temporal relations and constraints for clinical events in Electronic Health Records (EHR) represented in both structured and unstructured ways. The LifeFlow system is designed to support an interactive exploration of event sequences using visualization techniques. The combination of the two systems will provide a comprehensive environment for users to visualize inferred temporal relationships from EHR data. This paper discusses our preliminary efforts on connecting the two systems and the benefits we envision from such an environment.
EHR数据的事件序列表示、推理和可视化
对事件序列的有效分析和回答与时间相关的临床重要问题的能力可以加速几个领域的临床研究,如因果关系评估、决策支持系统和回顾性研究。基于临床叙述时间推理本体(CNTRO)的系统设计用于以结构化和非结构化方式表示电子健康记录(EHR)中临床事件的时间关系和约束的语义表示、注释和推断。LifeFlow系统旨在支持使用可视化技术对事件序列进行交互式探索。这两个系统的结合将为用户提供一个全面的环境来可视化从电子病历数据推断的时间关系。本文讨论了我们为连接这两个系统所做的初步努力,以及我们从这样一个环境中设想的好处。
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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