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<record>
  <title>An Expert Acquiring Method of Diagnosis and Senario Based on Maximum Knowledge Entropy </title>
  <journal>International Journal of Web Applications</journal>
  <author>Chao liu, Zuhua Jiang , Bin Chen, Yongwen Huang, Di Lu, Yi Ma </author>
  <volume>1</volume>
  <issue>2</issue>
  <year>2009</year>
  <doi></doi>
  <url>http://dline.info/ijwa/fulltext/v1n204.pdf</url>
  <abstract>The objective of this study is to present an Improved REX-1 method, rationalize the essential difference of Knowledge and information in medical practice. It aims at fi ghting for the effective and effi cient Expert-diagnosis process when various symptoms are to be distributed by the root knowledge mainbody in health care knowledge fl ow. The IREX-1 method can eliminate decision tree, creatively abstract knowledge entropy so as to improve the speed and accuracy of diagnosis- decision results. On this purpose, the authors use digestive diseases diagnosis prototype to justify the validity of this method, and do the comparison with renowned ID3,C4.5, ILA, ILA, 2 and original REX-1 algorithms when used in medical health care expert-diagnosis situation.</abstract>
</record>
