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- Title
高斯模糊积分及其在癌症诊断中的应用.
- Authors
王金凤; 田绪红; 王 希; 王文中
- Abstract
The classical fuzzy integral projects the data from high dimensional space into one dimensional space along a group of straight lines. In reality, the classical projection lines cannot cover the data with irregular distribution. This paper proposed a new fuzzy integral using Gaussian function as integrand which was called as Gaussian fuzzy integral (GFI). The projection with GFI could cover the most data along the Gaussian curves. It constructed a new classifier based on the Gaussian fuzzy integral and applied it to several benchmark datasets for testifying the performance. The results show that GFI can work better with FI' s characteristics and has better classification accuracy than classical FI. Finally, used GFI to classify the hepatitis B virus (HBV) gene data for cancer diagnosing. It selected all cases from the Wales Hospital of Hong Kong which included real cancer patients and uncertain ones. It tried to discern these cases clearly. The results show that GFI has optimal testing sensitivity for diagnosis. This index is more important for medicals than accuracy, which means it doesn't hope to miss any real patients as more as possible.
- Publication
Application Research of Computers / Jisuanji Yingyong Yanjiu, 2016, Vol 33, Issue 11, p3345
- ISSN
1001-3695
- Publication type
Article
- DOI
10.3969/j.issn.1001-3695.2016.11.032