Automatic detection of erythemato-squamous diseases using κ-means clustering

Journal of Medical Systems

Volumn 34, Issue 2, 2010, Pages 179-184

  Übeyli, Elif Derya ^a   Doǧdu, Erdoǧan ^a  

^a TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY   (Turkey)

Author keywords

Means clustering; Classification accuracy; Clustering; Erythemato squamous diseases

Indexed keywords

ARTICLE; ATTRIBUTABLE RISK; AUTOMATION; CLASSIFICATION ALGORITHM; CLINICAL FEATURE; CLUSTER ANALYSIS; DATA MINING; DIAGNOSTIC ACCURACY; DIFFERENTIAL DIAGNOSIS; DISEASE CLASSIFICATION; ERYTHEMA; ERYTHEMATOSQUAMOUS SKIN DISEASE; HISTOPATHOLOGY; HUMAN; KAPPA STATISTICS; LICHEN PLANUS; PITYRIASIS ROSEA; PSORIASIS; SEBORRHEIC DERMATITIS; SENSITIVITY AND SPECIFICITY; SKIN INFLAMMATION;

ALGORITHMS; CLUSTER ANALYSIS; DATA MINING; DERMATITIS, SEBORRHEIC; HUMANS; SENSITIVITY AND SPECIFICITY; SKIN DISEASES, PAPULOSQUAMOUS;

EID: 77950518669     PISSN: 01485598     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10916-008-9229-6     Document Type: Article

References (17)

1. Güvenir, H. A., Demiröz, G., and llter, N., Learning differential diagnosis of erythemato-squamous diseases using voting feature intervals. Artif. Intell. Med. 13:147-165, 1998. doi:10.1016/S0933-3657(98) 00028-1. (Pubitemid 28341691)
2. Baumgartner, C, Knowledge Discovery and Data Mining in Biomedicine, Thesis for Habilitation, University for Health Sciences, Medical Informatics and Technology, 2005.
3. Plant, C, Böhm, C, Tilg, B., and Baumgartner, C, Enhancing instance-based classification with local density: a new algorithm for classifying unbalanced biomedical data. Bioinformatics. 22:8981-8988, 2006. doi:10.1093/bioinformatics/btl027.
4. Baumgartner, C, Bohm, C, and Baumgartner, D., Modelling of classification rules on metabolic patterns including machine learning and expert knowledge. J. Biomed. Inform. 38:89-98, 2004. doi:10.1016/j.jbi.2004.08.009.
5. Margaret, H. D., Data Mining: Introductory and Advanced Topics, Prentice-Hall, ISBN: 0-13-088892-3, 2003.
6. Han, J., and Kamber, M., Data Mining: Concepts and Techniques, Morgan Kaufmann, 2001.
7. A Tutorial on Clustering Algorithms", see: http://www.elet.polimi. it/upload/matteucc/Clustering/tutorial-html/, 2006.
8. Drobics, M., Bodenhofer, U., and Winiwarter, W., Mining clusters and corresponding interpretable descriptions\a three-stage approach. Expert Syst. 19:4224-4234, 2002. doi:10.1111/1468-0394. 00207.
9. Polat, K., and Günes, S., An improved approach to medical data sets classification: artificial immune recognition system with fuzzy resource allocation mechanism. Expert Syst. 24:4252-4270, 2007. doi:10.1111/j.1468-0394. 2007.00432.x. (Pubitemid 47283813)
10. Wu, M.-N., Lin, C.-C, and Chang, C.-C, Brain tumor detection using color-based k-means clustering segmentation, intelligent information hiding and multimedia signal processing, 2007. IIHMSP 2007. Third International Conference on 2, 245-250, 26-28, 2007.
11. McLeod, P., and Verma, B., Clustering and Least Square Based Neural Technique for Learning and Identification of Suspicious Areas within Digital Mammograms, Conference on Computational Intelligence and Multimedia Applications, 2007. International Conference on, 1:190-194, 13-15 2007.
12. Bolshakova, N., and Azuaje, F., Estimating the number of clusters in DNA microarray data. Methods Inf. Med. 45:2153-2157, 2006.
13. Chekanov, S., JMinHEP\data mining framework for high-energy physics", see: http://projects.hepforge.org/jminhep/, 2006.
14. Übeyli, E. D., Multiclass support vector machines for diagnosis of erythemato-squamous diseases. Expert Syst. Appl. 35:41733-41740, 2008. doi:10.1016/j.eswa.2007.08.067.
15. Übeyli, E. D., and Güler, I., Automatic detection of erythemato-squamous diseases using adaptive neuro-fuzzy inference systems. Comput. Biol. Med. 35:5421-5433, 2005. doi:10.1016/j.compbiomed 2004.03.003. (Pubitemid 40354267)
16. Güvenir, H. A., and Emeksiz, N., An expert system for the differential diagnosis of erythemato-squamous diseases. Expert Syst. Appl. 18:143-239, 2000. doi:10.1016/S0957-4174(99)00049-4.
17. Nanni, L., An ensemble of classifiers for the diagnosis of erythemato-squamous diseases. Neurocomputing. 69:842-845, 2006. doi:10.1016/j.neucom.2005.09.007. (Pubitemid 43230387)