Multicriteria similarity models for medical diagnostic support algorithms

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.