Interactive knowledge validation in CBR for decision support in medicine

Authors:
Monica H. Ou;Geoff A. W. West;Mihai Lazarescu;Chris Clay
Affiliations:
Department of Computing, Curtin University of Technology, Perth, Western Australia, Australia;Department of Computing, Curtin University of Technology, Perth, Western Australia, Australia;Department of Computing, Curtin University of Technology, Perth, Western Australia, Australia;Royal Perth Hospital, Perth, Western Australia, Australia
Venue:
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
Year:
2005

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Abstract

In most case-based reasoning (CBR) systems there has been little research done on validating new knowledge, specifically on how previous knowledge differs from current knowledge by means of conceptual change. This paper proposes a technique that enables the domain expert who is non-expert in artificial intelligence (AI) to interactively supervise the knowledge validation process in a CBR system. The technique is based on formal concept analysis which involves a graphical representation and comparison of the concepts, and a summary description highlighting the conceptual differences. We propose a dissimilarity metric for measuring the degree of variation between the previous and current concepts when a new case is added to the knowledge base. The developed technique has been evaluated by a dermatology consultant, and has shown to be useful for discovering ambiguous cases and keeping the database consistent.