Interactive Exploration of Medical Data Sets

IF 1.3 Q4 ENGINEERING, BIOMEDICAL
H. Muller, K. Zatloukal, M. Streit, D. Schmalstieg
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引用次数: 6

Abstract

This paper describes an interactive data exploration system for molecular and clinical data in the field of personalized medicine. It addresses the essential but to date unsolved problem of how to identify connections between genetic variants and their corresponding diseases or the response to certain drugs and treatments, respectively. It is therefore necessary to connect genetic with clinical data in order to categorize specific subgroups of patients with certain disease features. The huge amount of data provided by molecular analytical methods (e.g. data on genetic alterations, proteomic or metabolomic data) can only be analyzed by applying statistical methods and bioinformatics. However, even standard methods of statistics and bioinformatics fail when the data is inhomogeneous - as is the case with clinical data - and when data structures are obscured by noise and dominant patterns. The structure of large medical data sets is made visible by using so called object- and attribute-glyphs, which can be arranged in a two dimensional space and synchronized with a set of visualization views.
医疗数据集的交互式探索
本文介绍了一种用于个性化医疗领域分子和临床数据的交互式数据探索系统。它解决了一个重要但迄今尚未解决的问题,即如何确定基因变异与其相应的疾病或对某些药物和治疗的反应之间的联系。因此,有必要将遗传与临床数据联系起来,以便对具有某些疾病特征的患者的特定亚群进行分类。分子分析方法提供的大量数据(如遗传改变数据、蛋白质组学或代谢组学数据)只能通过统计学方法和生物信息学进行分析。然而,即使是标准的统计学和生物信息学方法在数据不均匀时也会失败——就像临床数据的情况一样——并且当数据结构被噪声和主导模式所掩盖时。大型医疗数据集的结构可以通过使用所谓的对象和属性符号来显示,这些符号可以排列在二维空间中,并与一组可视化视图同步。
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来源期刊
CiteScore
2.80
自引率
6.20%
发文量
102
期刊介绍: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization is an international journal whose main goals are to promote solutions of excellence for both imaging and visualization of biomedical data, and establish links among researchers, clinicians, the medical technology sector and end-users. The journal provides a comprehensive forum for discussion of the current state-of-the-art in the scientific fields related to imaging and visualization, including, but not limited to: Applications of Imaging and Visualization Computational Bio- imaging and Visualization Computer Aided Diagnosis, Surgery, Therapy and Treatment Data Processing and Analysis Devices for Imaging and Visualization Grid and High Performance Computing for Imaging and Visualization Human Perception in Imaging and Visualization Image Processing and Analysis Image-based Geometric Modelling Imaging and Visualization in Biomechanics Imaging and Visualization in Biomedical Engineering Medical Clinics Medical Imaging and Visualization Multi-modal Imaging and Visualization Multiscale Imaging and Visualization Scientific Visualization Software Development for Imaging and Visualization Telemedicine Systems and Applications Virtual Reality Visual Data Mining and Knowledge Discovery.
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