基于双论域犹豫三角模糊多粒度粗糙集的疾病诊断

Disease Diagnosis Based on Hesitant Triangular Fuzzy Multigranulation Rough Sets over Two Universes

在临床决策领域,疾病诊断已成为较为复杂的决策问题之一。医疗专家在疾病诊断过程中不仅需要处理大量的不确定性信息,而且需要综合不同医疗专家的意见来给出最终的诊断结果。为了解决以上疾病诊断中普遍存在的不确定性数据分析以及群决策的问题,通过结合犹豫三角模糊集和多粒度粗糙集,提出双论域犹豫三角模糊多粒度粗糙集的概念。在此基础上,提出以疾病诊断为背景的决策模型并用算例阐述所提出模型的有效性。

In the area of clinical decision making, the issue of disease diagnosis has become one of the relatively complicated decision making problems. In disease diagnosis procedures, medical experts not only need to deal with numerous uncertain information, but also need to synthesize different expert＇s view for the sake of providing the final diagnostic results. In order to solve the problems of uncertain data analysis and group decision making that exist commonly in disease diagnosis processes, this paper proposes the concept of hesitant triangular fuzzy multigranulation rough sets over two universes through combining hesitant triangular fuzzy sets with multigranulation rough sets. Based on that, a decision making model under the background of disease diagnosis is presented, and an illustrative example is given to demonstrate its validity.