Background knowledge in diagnosis

Authors:
E. T. Keravnou;F. Dams;J. Washbrook;R. M. Dawood;C. M. Hall;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 WC1E 6BT, UK;Department of Computer Science, University College London, Gower Street, London WC1E 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:
Artificial Intelligence in Medicine
Year:
1992

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Abstract

A diagnostic framework in which there is a clear separation between the expertise per se and relevant background knowledge is discussed. We argue for the need to have an explicit representation of background knowledge. Background knowledge is domain foundational knowledge or common-sense knowledge; it is brought into play in the diagnostic context activated by the foreground knowledge, the diagnostic expertise. In the diagnostic framework discussed, background knowledge is of two types: foundational knowledge related to diagnostic findings and common-sense knowledge about time. The explicit representation and integration of expert and background knowledge is essential for achieving competent behaviour, both from the perspectives of the conversational context and the diagnostic performance of the system. The framework presented is being applied successfully to the domain of skeletal dysplasias.