Evaluation of visualisation techniques for meaningful representation of clinical classification data sets

Michael Tran, Jeewani Anupama Ginige, Christos Boulamatisi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Abstract. In the field of clinical classifications, such as ICD-10 (International Classification of Disease, version 10), there is a transition from paper-based books towards digital systems to have an open process, powered by collaboration. Most clinical classification systems contain massive volume of terms that are hierarchically organised. There are variety of approaches to visualise hierarchical data, in digital systems. In this paper, a selected set of technologies, such as tree views, tree view diagrams, force-directed graphs are investigated to evaluate the suitability of those to accommodate a large clinical classification data sets. Our findings suggest that tree view diagram is the most appropriate technique, due to its ability to accommodate the multi-parent structure of some clinical classifications, and represent large amounts of data in a visually appealing manner.
Original languageEnglish
Pages (from-to)145-150
Number of pages6
JournalStudies in Health Technology and Informatics
Volume252
DOIs
Publication statusPublished - 2018

Open Access - Access Right Statement

© 2018 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).

Keywords

  • International statistical classification of diseases and related health problems. 10th revision
  • classification
  • information storage and retrieval systems
  • visualization

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