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Using Generic Meta-Data-Models for Clustering Medical Data

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7451)

Abstract

We present a generic, meta-model based data storage system for research, clinical studies or disease registers, which is enabled to store data of almost arbitrary structure. The system is highly costumizeable and allows the user to set up a professional web-based data acquisition system including administration area, data input forms, overview tables and statistics within hours. Furthermore, we evaluated a number of clustering algorithms regarding their ability to cluster the stored datasets for similarity search and further statistical analysis.

Keywords

  • Cluster Algorithm
  • Hospital Information System
  • Medical Case
  • Consensus Cluster
  • Data Storage System

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Girardi, D., Giretzlehner, M., Küng, J. (2012). Using Generic Meta-Data-Models for Clustering Medical Data. In: Böhm, C., Khuri, S., Lhotská, L., Renda, M.E. (eds) Information Technology in Bio- and Medical Informatics. ITBAM 2012. Lecture Notes in Computer Science, vol 7451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32395-9_4

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  • DOI: https://doi.org/10.1007/978-3-642-32395-9_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32394-2

  • Online ISBN: 978-3-642-32395-9

  • eBook Packages: Computer ScienceComputer Science (R0)