Electronic Healthcare. Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers

Research Article

Collaborative Encoding of Asbru Clinical Protocols

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  • @INPROCEEDINGS{10.1007/978-3-642-23635-8_17,
        author={Marco Rospocher and Claudio Eccher and Chiara Ghidini and Rakebul Hasan and Andreas Seyfang and Antonella Ferro and Silvia Miksch},
        title={Collaborative Encoding of Asbru Clinical Protocols},
        proceedings={Electronic Healthcare. Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers},
        proceedings_a={E-HEALTH},
        year={2012},
        month={10},
        keywords={},
        doi={10.1007/978-3-642-23635-8_17}
    }
    
  • Marco Rospocher
    Claudio Eccher
    Chiara Ghidini
    Rakebul Hasan
    Andreas Seyfang
    Antonella Ferro
    Silvia Miksch
    Year: 2012
    Collaborative Encoding of Asbru Clinical Protocols
    E-HEALTH
    Springer
    DOI: 10.1007/978-3-642-23635-8_17
Marco Rospocher1, Claudio Eccher1, Chiara Ghidini1, Rakebul Hasan1, Andreas Seyfang2, Antonella Ferro3, Silvia Miksch2
  • 1: Fondazione Bruno Kessler
  • 2: Vienna University of Technology
  • 3: S. Chiara Hospital

Abstract

Encoding guidelines and treatment protocols in formal and computer-executable form is not a trivial task and requires the collaboration between clinicians and knowledge engineers. In this paper, we describe , a Semantic Media Wiki (SMW)-based tool for the collaborative encoding in a distributed environment of cancer treatment protocols in Asbru. exploits the great flexibility of SMW technology to mix unstructured information and semantic annotations, allowing to automatically generate the final formal model with minimal adaptation cost. uses forms and a graphical representation of the resulting plan hierarchy to help the encoding and the representation of the model. All these features render a natural candidate for small to medium scale modeling tasks, since the use of bigger systems may require a big adaptation and training effort. Moreover, our approach is not constrained to Asbru, but can be adapted to support other modeling languages.