Journal Published Online: 14 April 2022
Volume 51, Issue 1

A Hierarchical Visualization Fusion Method for Multi-information of Unconventional Mutation Medical Big Data



In the process of information fusion for medical data, there are some problems, such as low precision of data cleaning and more omission of duplicate data, which lead to the unsatisfactory effect of information fusion. This paper proposes a data collection strategy of a distributed network based on linear regression analysis, constructs a perceptual unconventional mutation data model by applying linear regression analysis method, and maintains the characteristics of perceptual data to realize data collection. The ID tags taken as data Transducer Identification of Strain gage are compared. Assuming that the TIDs of two data points are the same, that is, duplicate data are detected, the detected data set flows according to the method flow. To enhance the accuracy of data cleaning and avoid omission, the hierarchical visualization fusion method of radar maps is used to achieve multi-information fusion. It was found that the proposed method can clean the redundant data accurately and realize its efficient fusion.

Author Information

Tang, Yana
Department of electronic studies, Software Engineering Institute of Guangzhou, SEIG, Guangzhou, Guangdong, China
Zhang, Shilong
School of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, China
Pages: 10
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Stock #: JTE20210777
ISSN: 0090-3973
DOI: 10.1520/JTE20210777