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Interactive K-Means Clustering Method Based on User Behavior for Different Analysis Target in Medicine
Joint Authors
Yang, Lei
Dai, Yu
Yang, Yang
Zhang, Bin
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Clustering algorithm as a basis of data analysis is widely used in analysis systems.
However, as for the high dimensions of the data, the clustering algorithm may overlook the business relation between these dimensions especially in the medical fields.
As a result, usually the clustering result may not meet the business goals of the users.
Then, in the clustering process, if it can combine the knowledge of the users, that is, the doctor’s knowledge or the analysis intent, the clustering result can be more satisfied.
In this paper, we propose an interactive K-means clustering method to improve the user’s satisfactions towards the result.
The core of this method is to get the user’s feedback of the clustering result, to optimize the clustering result.
Then, a particle swarm optimization algorithm is used in the method to optimize the parameters, especially the weight settings in the clustering algorithm to make it reflect the user’s business preference as possible.
After that, based on the parameter optimization and adjustment, the clustering result can be closer to the user’s requirement.
Finally, we take an example in the breast cancer, to testify our method.
The experiments show the better performance of our algorithm.
American Psychological Association (APA)
Yang, Lei& Dai, Yu& Zhang, Bin& Yang, Yang. 2017. Interactive K-Means Clustering Method Based on User Behavior for Different Analysis Target in Medicine. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1142154
Modern Language Association (MLA)
Yang, Lei…[et al.]. Interactive K-Means Clustering Method Based on User Behavior for Different Analysis Target in Medicine. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1142154
American Medical Association (AMA)
Yang, Lei& Dai, Yu& Zhang, Bin& Yang, Yang. Interactive K-Means Clustering Method Based on User Behavior for Different Analysis Target in Medicine. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1142154
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142154