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Abstract
The paper presents a general procedure model for the identification of diagnostic medical patterns based on multicriteria assessment of similarity. A general similarity detection area was defined, in which a pattern recognition optimization problem was formulated. An exemplary algorithm supporting the process of determining the initial medical diagnosis based on the identified disease symptoms and risk factors is presented. The presented algorithm allows for determining a set of diseases from which there is none more probable, and their ranking.
Keywords: disease pattern; indicators and relations of similarity; pattern recognition; similarity; Tversky similarity model medical diagnosis
Received: 2012-11-13
Revised: 2013-1-9
Accepted: 2013-1-11
Published Online: 2013-02-23
Published in Print: 2013-03-01
©2013 by Walter de Gruyter Berlin Boston
