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Fusing Biomedical Multi-modal Data for Exploratory Data Analysis

  • Conference paper
Artificial Neural Networks – ICANN 2006 (ICANN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4132))

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Abstract

Data analysis in modern biomedical research has to integrate data from different sources, like microarray, clinical and categorical data, so called multi-modal data. The reef SOM, a metaphoric display, is applied and further improved such that it allows the simultaneous display of biomedical multi-modal data for an exploratory analysis. Visualizations of microarray, clinical, and category data are combined in one informative and entertaining image. The U-matrix of the SOM trained on microarray data is visualized as an underwater sea bed using color and texture. The clinical data and category data are integrated in the form of fish shaped glyphs. The resulting images are intuitive, entertaining and can easily be interpreted by the biomedical collaborator, since specific knowledge about the SOM algorithm is not required. Visual inspection enables the detection of interesting structural patterns in the multi-modal data when browsing through and zooming into the image. Results of such an analysis are presented for the van’t Veer data set.

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© 2006 Springer-Verlag Berlin Heidelberg

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Martin, C., grosse Deters, H., Nattkemper, T.W. (2006). Fusing Biomedical Multi-modal Data for Exploratory Data Analysis. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840930_83

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  • DOI: https://doi.org/10.1007/11840930_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38871-5

  • Online ISBN: 978-3-540-38873-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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