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We developed a visual mining system to support exploratory data analysis of multi-dimensional categorical EMR data.
In this study, we develop a visual mining system to support exploratory data analysis of multi-dimensional categorical EMR data.
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The objective of this research is to employ this approach to develop an interactive visual data mining application for 'omics expression data analyses that combines interactive visualization and statistical data mining.
In future geovisualization systems, the Grid could provide the infrastructure for transparent access to distributed data and computational resource; the semantic Web could be used to achieve automatic, dynamic, and consistent data integration; and visual data mining could be used to visually explore geographic data.
Visual data mining may overcome some of the flexibility problem often suffered by computer-centered data mining approaches.
Nevertheless, with the help of singularity theoretical progress in recent years, it is expected that visualization of large multivariate data featuring singular fibers will play essential role in visual data mining.
In this article, we describe techniques for visual data mining based on differential topology.
A visual data mining tool that facilitates reconstruction of transcription regulatory networks.
To design and develop visual data mining tools, an appropriate process must be followed.
The proposed process aims to model the visual data mining methods for supporting the dynamic decision-making.
This chapter reviews three major enabling technologies for intelligent information integration Grid computing, the semantic Web, and visual data mining.
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