A new health classification scheme based on fuzzy hesitant information

DOI

10.2991/ifsa-eusflat-15.2015.176How to use a DOI?

Keywords

Health measurement, Hesitant information, Geometric score, Geometric variance.

Abstract

The evaluation of the health status of a population is a key question in Health Policy. The measurement of the health status is a relevant process to keep and improve the countries’ level of economic development. In spite of this relevance, the current evaluation methodologies are not sufficiently well-defined either designed due to the fact that health is an inherently subjective notion. In order to overcome these drawbacks, first of all we propose a newer way to manage such uncertainty by means of the Fuzzy Logic Theory. Regarding the methodology, we develop a new approach to classify populations according to their health status based on hesitant fuzzy information. Additionally, we apply the proposed mechanism on real health data from 15 European countries.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - José Carlos Rodríguez-Alcantud
AU  - Rocío De Andrés Calle
AU  - Teresa González-Arteaga
PY  - 2015/06
DA  - 2015/06
TI  - A new health classification scheme based on fuzzy hesitant information
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  - 1245
EP  - 1252
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.176
DO  - 10.2991/ifsa-eusflat-15.2015.176
ID  - Rodríguez-Alcantud2015/06
ER  -