A Model to Classify the Disease Pattern Based on Similarity Degree Method

摘要：

in order to help human expert resolve the problem of diagnosing disease, we analyze the comparability and relativity between pattern recognition and disease diagnosis in terms of the solution means, and propose the theoretical model of disease-similarity-degrce pattern recognition on the basis of certainty factors vectors and fuzzy membership factors vectors, and its corresponding data structure mode. In addition, the software hierarchy of model and recognition algorithm, and its practice method are designed. Field experiment statistics demonstrate that: compared with the individual human expert, the proposed model be able to obtain a favorable accuracy rate of diagnosis over 85％, and reduce a rate of misdiagnosis effectively, which provided with a preferential comprehensive diagnosis performance.

关键词： disease classification expert system pattern recognition auxiliary diagnosis similarity degree

作者: Tan,Wenxue Xi,Jinju Wang,Xiping Bi,Yutong

作者单位: College of Computer Science and Technology Hunan University of Arts and Science Changde 415000,China College of Computer Science and Technology Hunan University of Aits and Science Changde 415000, Chin College of Economy and Management Hunan University of Arts and Science Changde 415000, China College of Computer Science and Technology Hunan University of Arts and Science Changde 415000, Chin

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 122-126

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）