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作者:

Zhang, Xin-Feng (Zhang, Xin-Feng.) | Shen, Lan-Sun (Shen, Lan-Sun.)

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摘要:

Several means of tongue manifestation information fusion are analyzed and compared and the means based on feature layer and decision layer and both are available in principle. The experiment results show the correct recognition rate based on them is low. It is very difficult to acquire a good result because of some factors such as much difference between two features. Rough set theory is a valid means to solve this problem. Some symptoms may be defined by the tongue manifestation features and some symptoms cannot be defined by the means based on the rough set theory, which avoids the error judgement in some sense and is crucial to the Chinese medical diagnosis. Rough set theory is hopeful to become an important means in the standardization of the symptom of Traditional Chinese Medicine (TCM).

关键词:

Classification (of information) Computer simulation Diagnosis Feature extraction Image analysis Medical imaging Medicine Rough set theory Standardization

作者机构:

  • [ 1 ] [Zhang, Xin-Feng]Signal and Information Processing Laboratory, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Shen, Lan-Sun]Signal and Information Processing Laboratory, Beijing University of Technology, Beijing 100022, China

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来源 :

Acta Electronica Sinica

ISSN: 0372-2112

年份: 2006

期: 4

卷: 34

页码: 717-721

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