An Intelligent Agent System using Multi-View Information Fusion (다각도 정보융합 방법을 이용한 지능형 에이전트 시스템)

Hyun-Sook Rhee (이현숙)

An Intelligent Agent System using Multi-View Information Fusion

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2014, 19(12), pp.11-19
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

Hyun-Sook Rhee ¹

¹동양미래대학교

Accredited

ABSTRACT

In this paper, we design an intelligent agent system with the data mining module and information fusionmodule as the core components of the system and investigate the possibility for the medical expertsystem. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data andproduces fuzzy cluster knowledge base. In the information fusion module and application module, theyserve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertaintydecision status or detection of asymmetry. We also present the experiment results on the BI-RADS-basedfeature data set selected form DDSM benchmark database. They show higher classification accuracy thanconventional methods and the feasibility of the system as a computer aided diagnosis system.

KEYWORDS

intelligent agent system, computer-aided diagnosis system, data mining, information fusion, feature data

Citation status

* References for papers published after 2023 are currently being built.

[journal] X. Wu / 2014 / Data Mining with Big Data / IEEE Trans on Knowledge and Data Engineering 26(1)

[journal] 김대수 / 2003 / Modeling and Design of Intelligent Agent System / International Journal of Control, Automation, and Systems / 제어·로봇·시스템학회 1(2) : 257~261

[confproc] D. Vidhate / 2012 / Cooperative Machine Learning with Information Fusion for Dynamic Decision Making in Diagnostic Applications / Int. Conf. on Advances in Mobile Network, Communication and its Applications

[journal] J. Tang / 2009 / Computer-Aided Detection and Diagnosis of Breast Cancer With Mammography : Recent Advances / IEEE Trans on Information Technology in Biomedicine 13(2)

[confproc] M. Heath / 2001 / The Digital Database for Screening Mammography / 5th IWDM / Medical Physics Publishers

[book] Mehmed Kantardzic / 2011 / Data Mining : Concepts, Models, and Algorithms / John Wiley & Sons

[journal] Z. Vlad / 2009 / Fuzzy Clustering in an Intelligent Agent for Diagnosis Establishment / Scientific Bulletin of the Petru Maior University of Tirgu Mures 6

[confproc] P. Vats / 2014 / A Noval Study of Fuzzy Clustering Algorithms for their Applications in Various Domains / JICTEE

[journal] 이현숙 / 2007 / A Feature Selection Method Based on Fuzzy Cluster Analysis / 정보처리학회논문지. 소프트웨어 및 데이터 공학 / 한국정보처리학회 14(2) : 135~140

[confproc] Wu, Y. / 2004 / Neural Network Fusion Strategies for Identifying Breast Masses / proc. of the IEEE International Joint Conference on Neural Networks(IEEE-IJCNN'2004)

[journal] R. Panchal / 2006 / "Characterization of breast abnormality patterns in digital mammograms using autoassociator neural network," in International Conference on Image Processing 2006, Part III / LNCS / Springer-Verlag 4234 : 127~136

[journal] Brijesh Verma / 2001 / A Computer-Aided Diagnosis System for Digital Mammograms Based on Fuzzy-Neural and Feature Extraction Techniques / IEEE Trans. on Information Technology in Biomedicine 5(1)

[confproc] M. Radovic / 2013 / Application of Data Mining Algorithms for Mammogram Classification / 13th conf. on Bioinformatics and Bioengineering(BIBE)

[confproc] L. Sun / 2010 / A Novel Classification Scheme for Breast Masses Based on Multi-view Information Fusion / 4th Int. Conf. on Bioinformatics &Biomedical Engineering (iCBBE)

[confproc] H. Zhao / 2011 / Classification of Breast Masses Based on Multi-view Information Fusion Using Multi-Agent Method / 5th Int. Conf. on Bioinformatics & Biomedical Engineering (iCBBE)

[web] / Reference URL / http://marathon.csee.usf.edu/Mammography/Database.html

[confproc] J. Y. Lo / 2003 / Computer-aided classification of breast microcalcification clusters: Merging of features from image processing and radiologists / Proc. SPIE 5032

[confproc] Dheeda J. / 2011 / Classification of Malignant and Benign Microcalcification Using SVM Classifier / Proc. of ICETECT

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Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65