Breast Cancer Digital Patient Model to Capture and Visualize Real World Data

N. Larburu, Mónica Arrúe, I. Macía, Jon Kerexeta, Naiara Muro
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Abstract

Digital revolution in health enables clinicians to access huge amount of data that can be exploited for decision making. However, the lack of integration of the various data sources, the existence of data sources not directly exploitable (e.g. free text, image, signals, genomic sequences) and the lack of digital data models (i.e. digital representation of the data) make such exploitation difficult. The development of effective Decision Support Systems (DSS) in concrete clinical contexts involves the development of appropriate and integrated representations of them, together with new paradigms for the exploitation, modeling and visualization of data oriented to decision-making. The European project DESIREE aims to contribute to the development of a system with these characteristics that has application to decision making by the Breast Committee. In particular, the visual analytics tool can contribute to the exploitation of clinical data in Breast Cancer.
乳腺癌数字患者模型捕捉和可视化真实世界的数据
卫生领域的数字革命使临床医生能够访问可用于决策的大量数据。然而,由于缺乏对各种数据源的整合,存在不能直接利用的数据源(例如自由文本、图像、信号、基因组序列)和缺乏数字数据模型(即数据的数字表示),使得这种利用变得困难。在具体的临床环境中,有效的决策支持系统(DSS)的发展涉及到适当的和集成的表示的发展,以及面向决策的数据的开发、建模和可视化的新范式。欧洲项目DESIREE旨在促进发展一个具有这些特点的系统,使其适用于乳房委员会的决策。特别是,可视化分析工具可以促进乳腺癌临床数据的开发。
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