Modelling diagnostic skills in the domain of skeletal dysplasias

Authors:
E. T. Keravnou;F. Dams;J. Washbrook;C. M. Hall;R. M. Dawood;D. Shaw
Affiliations:
Department of Computer Science, University of Cyprus, 75 Kallipoleos Str, Nicosia, T. T. 134, Cyprus;Department of Computer Science, University College London, Gower Street, London WCIE 6BT, UK;Department of Computer Science, University College London, Gower Street, London WCIE 6BT, UK;Department of Radiology, The Hospital for Sick Children, Great Ormond Street, London WCN 3JH, UK;Department of Radiology, The Hospital for Sick Children, Great Ormond Street, London WCN 3JH, UK;Department of Radiology, The Hospital for Sick Children, Great Ormond Street, London WCN 3JH, UK
Venue:
Computer Methods and Programs in Biomedicine
Year:
1994

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Abstract

The diagnostic model used in the medical expert system Skeletal Dysplasias Diagnostician (SDD) is discussed. The model aims to capture the diagnostic skills of domain experts. Such skills represent high level strategies which apply across different medical domains and hence the presented model is relatively generic. Preliminary evaluation of an earlier version of the diagnostic model, which yielded promising results, has led to a considerably improved model. A sample consultation given in an appendix illustrates most aspects of the current model. The paper concludes by giving the authors' practical insights into the knowledge engineering of medical diagnostic systems.