Modeling Trends in the Hierarchical Fuzzy System for Multi-criteria Evaluation of Medical Data

The paper presents the analysis and application of hierarchical fuzzy system to the problem of evaluation/ measurement of the rehabilitation effects in post-stroke patients. Healthy people constitute reference group. Prevalence and impact of the stroke-related disorders on Health-Related Quality of Life (HRQoL) as a recognized and important outcome after stroke is huge. Quick, valid and reliable assessment of HRQoL in people after stroke constitutes a worldwide significant problem for scientists and clinicians -there are many tools, but no one fulfills all requirements or has prevailing advantages. Evaluation model presented here is improved version of earlier attempts and applies the potential of fuzzy systems for linguistic modeling of rules. It provides a great advantage as there are experienced clinicians working on the improvement of the rehabilitation methods but there is no intuitive formal model to measure their effects. The innovative element here is the use of Ordered Fuzzy Number model. It is a good tool for modeling the trends in information used to create the fuzzy rules of small fuzzy systems which together form a hierarchical fuzzy evaluation model.