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首页> 外文会议>IEEE International Conference on Information Visualization >Multivariate Relational Visualization of Complex Clinical Datasets in a Critical Care Setting: A Data Visualization Interactive Prototype
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Multivariate Relational Visualization of Complex Clinical Datasets in a Critical Care Setting: A Data Visualization Interactive Prototype

机译：复杂临床数据集的多变量关系可视化在关键护理环境中：数据可视化交互式原型

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摘要

One mission of medical informatics is to provide physicians, nurses, and other health care providers with the technology and tools for interpreting large and diverse data sets, so that appropriate critical care decisions can be facilitated. Ideally, medical data visualization provides the means to transform data into information and contextual knowledge suitable for interpretation and decision-making [31, 9]. The authors propose a model through which data is organized into multivariate multidimensional critical care patient data visualizations (CPDV). It does this as the primary means to represent and manage complex context-based patient data at various user-defined temporal resolutions. Furthermore, user-defined spatial organization of multiple (clinically related) datasets allows rapid visualization of significant trends that are related to several co-variables. Currently, anticipated findings from usability testing support the notion that the proposed model will facilitate medical decision making in a critical care environment.
机译：医疗信息学的一个使命是为医生，护士和其他医疗保健提供者提供技术和工具，用于解释大型和多样化的数据集，从而可以促进适当的重大关心决策。理想情况下，医疗数据可视化提供了将数据转换为适合解释和决策的信息和上下文知识的方法[31,9]。作者提出了一种模型，通过该模型组织成多变量多维关键护理患者数据可视化（CPDV）。它确实是在各种用户定义的时间分辨率下表示和管理基于基于上下文的患者数据的主要方法。此外，多个（临床相关）数据集的用户定义的空间组织允许快速可视化与几个共变量相关的重要趋势。目前，可用性测试的预期结果支持拟议模型将促进在关键护理环境中的医学决策的概念。

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