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Volumn 46, Issue , 2016, Pages 139-144

Breast cancer classification using deep belief networks

Author keywords

Breast cancer diagnosis; CAD; Classification; Deep learning based classifier; Pattern recognition

Indexed keywords

BACKPROPAGATION; BAYESIAN NETWORKS; CLASSIFICATION (OF INFORMATION); COMPLEX NETWORKS; COMPUTER AIDED DESIGN; DIAGNOSIS; DISEASES; NEURAL NETWORKS; PATTERN RECOGNITION;

EID: 84946434304     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2015.10.015     Document Type: Article
Times cited : (446)

References (29)
  • 1
    • 0041339769 scopus 로고    scopus 로고
    • Supervised fuzzy clustering for the identification of fuzzy classifiers
    • Abonyi J., Szeifert F. Supervised fuzzy clustering for the identification of fuzzy classifiers Pattern Recognition Letters 24 2003 2195 2207
    • (2003) Pattern Recognition Letters , vol.24 , pp. 2195-2207
    • Abonyi, J.1    Szeifert, F.2
  • 2
    • 56349089940 scopus 로고    scopus 로고
    • Support vector machines combined with feature selection for breast cancer diagnosis
    • Akay M.F. Support vector machines combined with feature selection for breast cancer diagnosis Expert Systems With Applications 36 2009 3240 3247
    • (2009) Expert Systems With Applications , vol.36 , pp. 3240-3247
    • Akay, M.F.1
  • 6
    • 0036161034 scopus 로고    scopus 로고
    • Training Invariant Support Vector Machines
    • Decoste D., Schölkopf B. Training Invariant Support Vector Machines Machine Learning 46 2002 161 190
    • (2002) Machine Learning , vol.46 , pp. 161-190
    • Decoste, D.1    Schölkopf, B.2
  • 7
    • 84902456334 scopus 로고    scopus 로고
    • Computer-aided detection of breast cancer on mammograms: A swarm intelligence optimized wavelet neural network approach
    • Dheeba J., Singh N.A., Selvi S.T. Computer-aided detection of breast cancer on mammograms: A swarm intelligence optimized wavelet neural network approach Journal of Biomedical Informatics 49 2014 45 52
    • (2014) Journal of Biomedical Informatics , vol.49 , pp. 45-52
    • Dheeba, J.1    Singh, N.A.2    Selvi, S.T.3
  • 11
    • 84886563124 scopus 로고    scopus 로고
    • Accessed 03.09.14
    • Hinton, G.E.(2009a).Deep belief nets. < http://www.cs.toronto.edu/∼hinton/nipstutorial/nipstut3.pdf > Accessed 03.09.14.
    • (2009) Deep belief nets
    • Hinton, G.E.1
  • 12
  • 13
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • Hinton G.E., Osindero S., Teh Y.-W. A fast learning algorithm for deep belief nets Neural Computation 18 2006 1527 1554
    • (2006) Neural Computation , vol.18 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.-W.3
  • 17
    • 0032960792 scopus 로고    scopus 로고
    • Obtaining interpretable fuzzy classification rules from medical data
    • Nauck D., Kruse R. Obtaining interpretable fuzzy classification rules from medical data Artificial Intelligence in Medicine 16 1999 149 169
    • (1999) Artificial Intelligence in Medicine , vol.16 , pp. 149-169
    • Nauck, D.1    Kruse, R.2
  • 18
    • 84946420866 scopus 로고    scopus 로고
    • Accessed 03.09.14
    • Palm, R.B.(2012). Deep learning toolbox. < https://github.com/rasmusbergpalm/DeepLearnToolbox > Accessed 03.09.14.
    • (2012) Deep learning toolbox
    • Palm, R.B.1
  • 19
    • 84864679424 scopus 로고    scopus 로고
    • Classification of breast cancer by comparing backpropagation training algorithm
    • Paulin F. Classification of breast cancer by comparing backpropagation training algorithm Intenational Journal on Computer Science and Engineering 3 2011 327 332
    • (2011) Intenational Journal on Computer Science and Engineering , vol.3 , pp. 327-332
    • Paulin, F.1
  • 21
    • 34249317613 scopus 로고    scopus 로고
    • Breast cancer diagnosis using least square support vector machine
    • Polat K., Günes S. Breast cancer diagnosis using least square support vector machine Digital Signal Processing 17 2007 694 701
    • (2007) Digital Signal Processing , vol.17 , pp. 694-701
    • Polat, K.1    Günes, S.2
  • 24
    • 84910651844 scopus 로고    scopus 로고
    • Deep learning in neural networks: An overview
    • Schmidhuber J. Deep learning in neural networks: An overview Neural Networks 61C 2014 85 117
    • (2014) Neural Networks , vol.61 C , pp. 85-117
    • Schmidhuber, J.1
  • 25
    • 0034159928 scopus 로고    scopus 로고
    • Generating concise and accurate classification rules for breast cancer diagnosis
    • Setiono R. Generating concise and accurate classification rules for breast cancer diagnosis Artificial Intelligence in Medicine 18 2000 205 219
    • (2000) Artificial Intelligence in Medicine , vol.18 , pp. 205-219
    • Setiono, R.1
  • 27
    • 33947653184 scopus 로고    scopus 로고
    • Implementing automated diagnostic systems for breast cancer detection
    • Übeyli E.D. Implementing automated diagnostic systems for breast cancer detection Expert Systems With Applications 33 2007 1054 1062
    • (2007) Expert Systems With Applications , vol.33 , pp. 1054-1062
    • Übeyli, E.D.1
  • 28
    • 84946420868 scopus 로고    scopus 로고
    • (original). Accessed 03.09.14
    • Wisconsin breast cancer dataset (WBCD) (2014). (original). Accessed 03.09.14 < https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Original%29 >.
    • (2014) Wisconsin breast cancer dataset (WBCD)
  • 29
    • 84946420869 scopus 로고    scopus 로고
    • Accessed 03.09.14
    • World cancer research fund. (2014). < http://www.wcrf.org/int/cancer-facts-figures/data-specific-cancers/breast-cancer-statistics > Accessed 03.09.14.
    • (2014)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.