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Diagnosis of nephropathia epidemica by adaptation through Lukasiewicz inference
Department of Computer Science, Åbo Akademi, Åbo, Finland.
University of Turku, Department of Clinical Chemistry, Central Laboratory, Turku University Central Hospital, SF-20520 Turku, Finland.
1990 (English)In: Computational Intelligence, III: Proceedings of the International Symposium "Computational Intelligence 90", Milan, Italy, 24-28 September, 1990. / [ed] Nick Cerone, Francesco Gardin, co-editor, George Valle, Amsterdam, The Netherlands: Elsevier, 1990, 237-246 p.Chapter in book (Refereed)
Abstract [en]

This paper describes a method how to arrive at a medical expert system (as a knowledge based system) to support physicians in classifying patients in diagnosis of Nephropathia epidemica (NE). We thereby present a link between Lukasiewicz inference and learning in neural nets, as a formal connection between uncertainty in logical implication and synaptic weights. The system presented uses clinical findings and laboratory investigations to arrive at predictions whether or not patients suffer from NE. Although we are willing to call our system a medical expert system, it could equally well be called a decision support system, this being more in spirit to what such a system really offers a physician.

Place, publisher, year, edition, pages
Amsterdam, The Netherlands: Elsevier, 1990. 237-246 p.
Keyword [en]
Haemorrhagic fever, neural nets, Lukasiewicz inference, incremental evidence
National Category
Computer Science Other Chemical Engineering
Identifiers
URN: urn:nbn:se:umu:diva-80548ISBN: 0-444-89118-8 (print)OAI: oai:DiVA.org:umu-80548DiVA: diva2:650367
Conference
International Symposium "Computational Intelligence 90", Milan, Italy, 24-28 September, 1990.
Available from: 2013-09-20 Created: 2013-09-20 Last updated: 2014-02-14Bibliographically approved

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CiteExportLink to record
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  • apa
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  • nn-NB
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