Improving medical decisions under incomplete data using interval–valued fuzzy aggregation
Patryk Zywica, Andrzej Wójtowicz, Anna Stachowiak, Krzysztof Dyczkowski
Available Online June 2015.
- https://doi.org/10.2991/ifsa-eusflat-15.2015.83How to use a DOI?
- Missing data, incomplete information, decision-making, uncertainty, aggregation, intervalvalued fuzzy sets, supporting medical diagnosis
- We state a problem concerning how to make an effective and proper decision in the presence of data incompleteness. As an example we consider a medical diagnostic system where the problem of missing data is commonly encountered. We propose and evaluate an approach that makes it possible to reduce the influence of missing data on the final result and to improve the quality of the decision. The process involves interval-valued fuzzy set modelling, uncertaintification of classical methods, and finally aggregation of the incomplete results. It was verified that the aggregation results in meaningful and accurate decisions despite the missing data.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Patryk Zywica AU - Andrzej Wójtowicz AU - Anna Stachowiak AU - Krzysztof Dyczkowski PY - 2015/06 DA - 2015/06 TI - Improving medical decisions under incomplete data using interval–valued fuzzy aggregation BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 577 EP - 584 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.83 DO - https://doi.org/10.2991/ifsa-eusflat-15.2015.83 ID - Zywica2015/06 ER -