Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 1
147-154

Auxiliary diagnosis model of breast mass based on improved dynamic ensemble selection algorithm

Liu Zihua1a,1b
Zheng Handong1a,1c
Liu Weiyong2
1. a. School of Management, b. Engineering Research Center of Intelligent decision & Information System Technology of Ministry of Education, c. Key Laboratory of Process Optimization & Intelligent Decision-Making of Ministry of Education, Hefei University of Technology, Hefei 230009, China
2. Dept. of Ultrasound, the First Affiliated Hospital of University of Science & Technology of China, Hefei 230036, China
DOI: 10.19734/j.issn.1001-3695.2022.05.0259

Abstract

In the dynamic ensemble selection algorithm, the region of competence of the test sample was composed of fixed samples, which would affect the classifier selection. Therefore, this paper proposed the DES-DCR-CIER algorithm based on dynamic region of competence strategy. Firstly, this algorithm used the heterogeneous classifier to generate the base classifier pool to deal with the problem that the difference between the homogeneous ensemble classifiers was little and the number of heterogeneous ensemble classifiers was small. Next, it applied three steps including the mutual K-nearest neighbor with adaptive distance algorithm, approaching the distance center of the sample set and removing the class edge samples to determine the dynamic region of competence of the test sample and used overall complementarity index to select a set of classifiers. Finally, it synthesized the classifiers by the ER rule to get integration. Experiments on the diagnosis data of breast mass from 8 sonographers in a tertiary hospital in Hefei, Anhui Province and American Wisconsin Breast Cancer Diagnostic data set show that the diagnostic model based on the DES-DCR-CIER algorithm has better accuracy.

Foundation Support

国家自然科学基金资助项目(72171066)
中央高校基本科研业务费专项资金资助项目(JS2021ZSPY0020,JZ2021HGQA0210)
NSFC-浙江两化融合联合基金资助项目(U1709215)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.05.0259
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 1
Section: Algorithm Research & Explore
Pages: 147-154
Serial Number: 1001-3695(2023)01-024-0147-08

Publish History

[2022-08-11] Accepted Paper
[2023-01-05] Printed Article

Cite This Article

刘子华, 郑汉东, 刘卫勇. 基于改进动态集成选择算法的乳腺肿块辅助诊断模型 [J]. 计算机应用研究, 2023, 40 (1): 147-154. (Liu Zihua, Zheng Handong, Liu Weiyong. Auxiliary diagnosis model of breast mass based on improved dynamic ensemble selection algorithm [J]. Application Research of Computers, 2023, 40 (1): 147-154. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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