Table of Contents Author Guidelines Submit a Manuscript
Computational and Mathematical Methods in Medicine
Volume 2015, Article ID 292710, 12 pages
Research Article

A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses

Chao Zhang,1,2 Deyu Li,1,2 and Yan Yan3

1School of Computer and Information Technology, Shanxi University, Taiyuan, Shanxi 030006, China
2Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Taiyuan, Shanxi 030006, China
3School and Hospital of Stomatology, Peking University, Beijing 100089, China

Received 24 August 2015; Accepted 12 November 2015

Academic Editor: Seiya Imoto

Copyright © 2015 Chao Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In medical science, disease diagnosis is one of the difficult tasks for medical experts who are confronted with challenges in dealing with a lot of uncertain medical information. And different medical experts might express their own thought about the medical knowledge base which slightly differs from other medical experts. Thus, to solve the problems of uncertain data analysis and group decision making in disease diagnoses, we propose a new rough set model called dual hesitant fuzzy multigranulation rough set over two universes by combining the dual hesitant fuzzy set and multigranulation rough set theories. In the framework of our study, both the definition and some basic properties of the proposed model are presented. Finally, we give a general approach which is applied to a decision making problem in disease diagnoses, and the effectiveness of the approach is demonstrated by a numerical example.