Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (8): 249-255.DOI: 10.3778/j.issn.1002-8331.1901-0061

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Visual Multiple Attribute Decision-Making Method for Medical Assistant Diagnosis

CHEN Jie, CHENG Sheng, XU Meng, SHI Haobin   

  1. 1.The China Manned Space Engineering Office, Beijing 100083, China
    2.Software R&D Center, China Aerospace Science and Technology Corporation, Beijing 100094, China
    3.School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China
  • Online:2020-04-15 Published:2020-04-14



  1. 1.中国载人航天办公室,北京 100083
    2.中国航天科技集团公司 软件研发中心,北京 100094
    3.西北工业大学 计算机学院,西安 710072


Traditional decision-making of medical assistant diagnosis usually relies on experience of experts to make decisions on alternatives, but this method relies on experience of experts and may bring subjective fatigue to experts. Based on the theory of multi-attribute decision-making, a visual multi-attribute decision-making method is proposed in this paper. Firstly, ordered weighted geometric operators are used to sort the data in descending order to generate an ordered sequence. Secondly, the ordered data is transformed into nodes in complex networks through visual graph theory, and the ordered data is visualized through the connection relationship between nodes in complex networks. Finally, law of Coulomb is used for reference, the ordered data is visualized by using nodes in complex networks. The support function is set by the distance between the nodes and the value of the node to describe the support degree of the node. The feasibility and validity of the visual multi-attribute decision-making method proposed in this paper are verified by two cases of etiological diagnosis and disease diagnosis.

Key words: medical assistant diagnosis, multiple attribute decision making, complex network, support function



关键词: 医疗辅助诊断, 多属性决策, 复杂网络, 支持度函数