用于患者分层和生物标志物发现的可视化分析方法

S. Alemzadeh, F. Kromp, B. Preim, S. Taschner-Mandl, K. Bühler
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引用次数: 0

摘要

我们介绍了一个可视化的分析工具,用于癌症患者的风险分层和生物标志物的发现。目前,用于联合分析该领域多种生物和临床信息的工具不足或缺乏。我们的工具填补了这一空白,使生物医学专家能够探索癌症患者队列的数据集。通过使用多种协调的可视化技术,可以对各种数据类型执行嵌套的可视化查询,从而通过识别离散的子队列来生成/证明假设。我们通过一个涉及生物医学研究人员的案例研究展示了discoVA的效用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Visual Analytics Approach for Patient Stratification and Biomarker Discovery
We introduce discoVA as a visual analytics tool for the refinement of risk stratification of cancer patients and biomarker discovery. Currently, tools for the joint analysis of multiple biological and clinical information in this field are insufficient or lacking. Our tool fills this gap by enabling bio-medical experts to explore datasets of cancer patient cohorts. By using multiple coordinated visualization techniques, nested visual queries on various data types can be performed to generate/prove a hypothesis by identifying discrete sub-cohorts. We demonstrated the utility of discoVA by a case study involving bio-medical researchers.
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