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Volumn 23, Issue SUPPL1, 2013, Pages 55-72

Superior neuro-fuzzy classification systems

Author keywords

Adaptive neuro fuzzy inference system (ANFIS); Feature selection (FS); Linguistic hedge (LH); Scaled conjugate gradient; Subtractive clustering; Takagi Sugeno Kang (TSK) fuzzy inference system

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; FUZZY INFERENCE SYSTEMS; LINGUISTIC HEDGES; SCALED CONJUGATE GRADIENTS; SUBTRACTIVE CLUSTERING;

EID: 84888823925     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-012-1231-8     Document Type: Article
Times cited : (27)

References (111)
  • 1
    • 0035841036 scopus 로고    scopus 로고
    • Feature extraction and classification of breast cancer on dynamic magnetic resonance imaging using artificial neural network
    • Abdolmaleki P, Buadu LD, Naderimansh H (2001) Feature extraction and classification of breast cancer on dynamic magnetic resonance imaging using artificial neural network. Cancer Lett 171(2): 183-191.
    • (2001) Cancer Lett , vol.171 , Issue.2 , pp. 183-191
    • Abdolmaleki, P.1    Buadu, L.D.2    Naderimansh, H.3
  • 2
    • 0031442386 scopus 로고    scopus 로고
    • Neural network analysis of breast cancer from MRI findings
    • Abdolmaleki P, Buadu LD, Murayama S et al (1997) Neural network analysis of breast cancer from MRI findings. Radiat Med 15(5): 283-293.
    • (1997) Radiat Med , vol.15 , Issue.5 , pp. 283-293
    • Abdolmaleki, P.1    Buadu, L.D.2    Murayama, S.3
  • 3
    • 0036275180 scopus 로고    scopus 로고
    • An evolutionary artificial neural networks approach for breast cancer diagnosis
    • Abbass HA (2002) An evolutionary artificial neural networks approach for breast cancer diagnosis. Artif Intell Med 25(3): 265-281.
    • (2002) Artif Intell Med , vol.25 , Issue.3 , pp. 265-281
    • Abbass, H.A.1
  • 6
    • 80052301880 scopus 로고    scopus 로고
    • 978-953-7619-92-3, Vienna: IN-TECH
    • Azar AT (2010) Fuzzy Systems. IN-TECH, Vienna. ISBN 978-953-7619-92-3.
    • (2010) Fuzzy Systems
    • Azar, A.T.1
  • 7
    • 79957994579 scopus 로고    scopus 로고
    • Adaptive neuro-fuzzy systems
    • A. T. Azar (Ed.), Austria: IN-TECH
    • Azar AT (2010) Adaptive neuro-fuzzy systems. In: Azar AT (ed) Fuzzy systems. IN-TECH, Austria, pp 85-110.
    • (2010) Fuzzy Systems , pp. 85-110
    • Azar, A.T.1
  • 8
    • 0037209504 scopus 로고    scopus 로고
    • Breast cancer detection using rank-nearest neighbor classification rules
    • Baguia C (2003) Breast cancer detection using rank-nearest neighbor classification rules. Pattern Recogn 36(1): 367-381.
    • (2003) Pattern Recogn , vol.36 , Issue.1 , pp. 367-381
    • Baguia, C.1
  • 9
    • 0001209372 scopus 로고
    • Accelerated backpropagation learning: two optimization methods
    • Battiti R (1989) Accelerated backpropagation learning: two optimization methods. Complex Syst 3(4): 331-342.
    • (1989) Complex Syst , vol.3 , Issue.4 , pp. 331-342
    • Battiti, R.1
  • 10
    • 33746862009 scopus 로고    scopus 로고
    • Neuro-fuzzy system for prostate cancer diagnosis
    • Benecchi L (2009) Neuro-fuzzy system for prostate cancer diagnosis. Urology 68(2): 357-361.
    • (2009) Urology , vol.68 , Issue.2 , pp. 357-361
    • Benecchi, L.1
  • 11
    • 0021583718 scopus 로고
    • FCM: the Fuzzy C-Means Clustering Algorithm
    • Bezdek JC, Ehrlich R, Full W (1984) FCM: the Fuzzy C-Means Clustering Algorithm. Comput Geosci 10(2-3): 191-203.
    • (1984) Comput Geosci , vol.10 , Issue.2-3 , pp. 191-203
    • Bezdek, J.C.1    Ehrlich, R.2    Full, W.3
  • 12
    • 0026655955 scopus 로고
    • Analysis of cancers missed at screening mammography
    • Bird RE, Wallace TW, Yankaskas BC (1992) Analysis of cancers missed at screening mammography. Radiology 184(3): 613-617.
    • (1992) Radiology , vol.184 , Issue.3 , pp. 613-617
    • Bird, R.E.1    Wallace, T.W.2    Yankaskas, B.C.3
  • 14
    • 0031047117 scopus 로고    scopus 로고
    • Artificial neural networks improve the accuracy of cancer survival prediction
    • Burke HB, Goodman PH, Rosen DB et al (1997) Artificial neural networks improve the accuracy of cancer survival prediction. Cancer 79(4): 857-862.
    • (1997) Cancer , vol.79 , Issue.4 , pp. 857-862
    • Burke, H.B.1    Goodman, P.H.2    Rosen, D.B.3
  • 15
    • 70350534585 scopus 로고    scopus 로고
    • Speeding up the scaled conjugate gradient algorithm and its application in neuro-fuzzy classifier training
    • Cetişli B, Barkana A (2010) Speeding up the scaled conjugate gradient algorithm and its application in neuro-fuzzy classifier training. Soft Comput 14(4): 365-378.
    • (2010) Soft Comput , vol.14 , Issue.4 , pp. 365-378
    • Cetişli, B.1    Barkana, A.2
  • 16
    • 77951152137 scopus 로고    scopus 로고
    • Development of an adaptive neuro-fuzzy classifier using linguistic hedges: part 1
    • Cetişli B (2010) Development of an adaptive neuro-fuzzy classifier using linguistic hedges: part 1. Expert Syst Appl 37(8): 6093-6101.
    • (2010) Expert Syst Appl , vol.37 , Issue.8 , pp. 6093-6101
    • Cetişli, B.1
  • 17
    • 77951206911 scopus 로고    scopus 로고
    • The effect of linguistic hedges on feature selection: part 2
    • Cetişli B (2010) The effect of linguistic hedges on feature selection: part 2. Expert Syst Appl 37(8): 6102-6108.
    • (2010) Expert Syst Appl , vol.37 , Issue.8 , pp. 6102-6108
    • Cetişli, B.1
  • 19
    • 0142120449 scopus 로고    scopus 로고
    • Computer-aided detection and classification of microcalcifications in mammograms: a survey
    • Cheng HD, Cai X, Chen X, Hu L, Lou X (2003) Computer-aided detection and classification of microcalcifications in mammograms: a survey. Pattern Recogn 36(12): 2967-2991.
    • (2003) Pattern Recogn , vol.36 , Issue.12 , pp. 2967-2991
    • Cheng, H.D.1    Cai, X.2    Chen, X.3    Hu, L.4    Lou, X.5
  • 20
    • 84974743850 scopus 로고
    • Fuzzy model identification based on cluster estimation
    • Chiu SL (1994) Fuzzy model identification based on cluster estimation. J Intell Fuzzy Syst 2(3): 267-278.
    • (1994) J Intell Fuzzy Syst , vol.2 , Issue.3 , pp. 267-278
    • Chiu, S.L.1
  • 21
    • 2342646229 scopus 로고    scopus 로고
    • Mining the breast cancer pattern using artificial neural networks and multivariate adaptive regression splines
    • Chou SM, Lee TS, Shao YE, Chen IF (2004) Mining the breast cancer pattern using artificial neural networks and multivariate adaptive regression splines. Expert Syst Appl 27(1): 133-142.
    • (2004) Expert Syst Appl , vol.27 , Issue.1 , pp. 133-142
    • Chou, S.M.1    Lee, T.S.2    Shao, Y.E.3    Chen, I.F.4
  • 22
    • 0033903664 scopus 로고    scopus 로고
    • Unsupervised stratification of cross-validation for accuracy estimation
    • Diamantidis NA, Karlis D, Giakoumakis EA (2000) Unsupervised stratification of cross-validation for accuracy estimation. Artif Intell 116(1-2): 1-16.
    • (2000) Artif Intell , vol.116 , Issue.1-2 , pp. 1-16
    • Diamantidis, N.A.1    Karlis, D.2    Giakoumakis, E.A.3
  • 23
    • 0028005364 scopus 로고
    • Prediction of breast cancer malignancy using an artificial neural network
    • Floyd CE, Lo JY, Yun AJ et al (1994) Prediction of breast cancer malignancy using an artificial neural network. Cancer 74(11): 2944-2948.
    • (1994) Cancer , vol.74 , Issue.11 , pp. 2944-2948
    • Floyd, C.E.1    Lo, J.Y.2    Yun, A.J.3
  • 25
    • 0000615669 scopus 로고
    • Function minimization by conjugate gradients
    • Fletcher R, Reeves CM (1964) Function minimization by conjugate gradients. Comput J 7(2): 149-154.
    • (1964) Comput J , vol.7 , Issue.2 , pp. 149-154
    • Fletcher, R.1    Reeves, C.M.2
  • 26
    • 18544399463 scopus 로고    scopus 로고
    • Evolving artificial neural networks for screening features from mammograms
    • Fogel DB, Wasson EC, Boughton EM, Porto VW (1998) Evolving artificial neural networks for screening features from mammograms. Artif Intell Med 14(3): 317-326.
    • (1998) Artif Intell Med , vol.14 , Issue.3 , pp. 317-326
    • Fogel, D.B.1    Wasson, E.C.2    Boughton, E.M.3    Porto, V.W.4
  • 27
    • 33847674996 scopus 로고    scopus 로고
    • Resampling methods for parameter-free and robust feature selection with mutual information
    • Francois D, Rossi F, Wertz V, Verleysen M (2007) Resampling methods for parameter-free and robust feature selection with mutual information. Neurocomputing 70(7-9): 1276-1288.
    • (2007) Neurocomputing , vol.70 , Issue.7-9 , pp. 1276-1288
    • Francois, D.1    Rossi, F.2    Wertz, V.3    Verleysen, M.4
  • 28
    • 0000841115 scopus 로고    scopus 로고
    • Neural networks approach to early breast cancer detection
    • Furundzic D, Djordjevic M, Bekic AJ (1998) Neural networks approach to early breast cancer detection. J Syst Archit 44(8): 617-633.
    • (1998) J Syst Archit , vol.44 , Issue.8 , pp. 617-633
    • Furundzic, D.1    Djordjevic, M.2    Bekic, A.J.3
  • 30
    • 78549266472 scopus 로고    scopus 로고
    • Adaptive Neuro-Fuzzy Inference System (ANFIS) in Modelling Breast Cancer Survival
    • July, 18-23, CCIB, Barcelona, Spain
    • Hamdan H, Garibaldi JM (2010) Adaptive Neuro-Fuzzy Inference System (ANFIS) in Modelling Breast Cancer Survival. WCCI 2010 IEEE World Congress on Computational Intelligence, July, 18-23, CCIB, Barcelona, Spain, pp 1-8.
    • (2010) WCCI 2010 IEEE World Congress on Computational Intelligence , pp. 1-8
    • Hamdan, H.1    Garibaldi, J.M.2
  • 31
    • 0001138328 scopus 로고
    • A k-means clustering algorithm
    • Hartigan JA, Wong MA (1979) A k-means clustering algorithm. Appl Stat 28(1): 100-108.
    • (1979) Appl Stat , vol.28 , Issue.1 , pp. 100-108
    • Hartigan, J.A.1    Wong, M.A.2
  • 34
    • 78349249743 scopus 로고    scopus 로고
    • Feature-Weighted Mountain Method with Its Application to Color Image Segmentation
    • Springer-Verlag Berlin Heidelberg
    • Hung WL, Yang MS, Yu J, Hwang CM. (2010) Feature-Weighted Mountain Method with Its Application to Color Image Segmentation. RSKT'10, LNAI 6401, pp 537-544. Springer-Verlag Berlin Heidelberg.
    • (2010) RSKT'10, LNAI 6401 , pp. 537-544
    • Hung, W.L.1    Yang, M.S.2    Yu, J.3    Hwang, C.M.4
  • 35
    • 33645268110 scopus 로고    scopus 로고
    • Diagnostic application of serum protein pattern and artificial neural network software in breast cancer
    • Hu Y, Zhang SZ, Yu JK, Liu J, Zheng S, Hu X (2005) Diagnostic application of serum protein pattern and artificial neural network software in breast cancer. Ai Zheng 24(1): 67-71.
    • (2005) Ai Zheng , vol.24 , Issue.1 , pp. 67-71
    • Hu, Y.1    Zhang, S.Z.2    Yu, J.K.3    Liu, J.4    Zheng, S.5    Hu, X.6
  • 36
    • 32644440353 scopus 로고    scopus 로고
    • Information-preserving hybrid data reduction based on fuzzy-rough techniques
    • Hu Q, Yu D, Xie Z (2006) Information-preserving hybrid data reduction based on fuzzy-rough techniques. Pattern Recogn Lett 27(5): 414-423.
    • (2006) Pattern Recogn Lett , vol.27 , Issue.5 , pp. 414-423
    • Hu, Q.1    Yu, D.2    Xie, Z.3
  • 37
    • 0033894519 scopus 로고    scopus 로고
    • Fast detection of masses in computer aided mammography
    • Ioanna C, Evalgelos D, George K (2000) Fast detection of masses in computer aided mammography. IEEE Signal Process Mag 17(1): 54-64.
    • (2000) IEEE Signal Process Mag , vol.17 , Issue.1 , pp. 54-64
    • Ioanna, C.1    Evalgelos, D.2    George, K.3
  • 38
    • 79955369556 scopus 로고    scopus 로고
    • An efficient automatic mass classification method in digitized mammograms using artificial neural network
    • Islam MJ, Ahmadi M, Sid-Ahmed MA (2010) An efficient automatic mass classification method in digitized mammograms using artificial neural network. Int J Artif Intell Appl (IJAIA) 1(3): 1-13.
    • (2010) Int J Artif Intell Appl (IJAIA) , vol.1 , Issue.3 , pp. 1-13
    • Islam, M.J.1    Ahmadi, M.2    Sid-Ahmed, M.A.3
  • 39
    • 12444281823 scopus 로고    scopus 로고
    • A comparative study of fuzzy classification methods on breast cancer data
    • Jain R, Abraham A (2004) A comparative study of fuzzy classification methods on breast cancer data. Australas Phys Eng Sci Med 27(4): 213-218.
    • (2004) Australas Phys Eng Sci Med , vol.27 , Issue.4 , pp. 213-218
    • Jain, R.1    Abraham, A.2
  • 41
    • 0027601884 scopus 로고
    • ANFIS: adaptive-network-based fuzzy inference system
    • Jang JSR (1993) ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybern 23(3): 665-685.
    • (1993) IEEE Trans Syst Man Cybern , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.S.R.1
  • 42
    • 0029273384 scopus 로고
    • Neuro-fuzzy modeling and control
    • Jang JSR, Sun CT (1995) Neuro-fuzzy modeling and control. Proc IEEE 83(3): 378-406.
    • (1995) Proc IEEE , vol.83 , Issue.3 , pp. 378-406
    • Jang, J.S.R.1    Sun, C.T.2
  • 45
    • 1842856149 scopus 로고    scopus 로고
    • A combined neural network and decision trees model for prognosis of breast cancer relapse
    • Jerez-Aragonés JM, Gomez-Ruiz JA, Ramos-Jiménez G et al (2003) A combined neural network and decision trees model for prognosis of breast cancer relapse. Artif Intell Med 27(1): 45-63.
    • (2003) Artif Intell Med , vol.27 , Issue.1 , pp. 45-63
    • Jerez-Aragonés, J.M.1    Gomez-Ruiz, J.A.2    Ramos-Jiménez, G.3
  • 46
    • 0000293377 scopus 로고
    • Backpropagation learning for multi-layer feed-forward neural networks using the conjugate gradient method
    • Johansson EM, Dowla EU, Goodman DM (1991) Backpropagation learning for multi-layer feed-forward neural networks using the conjugate gradient method. Int J Neural Syst 2(4): 291-302.
    • (1991) Int J Neural Syst , vol.2 , Issue.4 , pp. 291-302
    • Johansson, E.M.1    Dowla, E.U.2    Goodman, D.M.3
  • 48
    • 34247124366 scopus 로고    scopus 로고
    • Breast cancer diagnosis using statistical neural networks
    • Kiyan T, Yildirim T (2004) Breast cancer diagnosis using statistical neural networks. J Elect Electron Eng 4(2): 1149-1153.
    • (2004) J Elect Electron Eng , vol.4 , Issue.2 , pp. 1149-1153
    • Kiyan, T.1    Yildirim, T.2
  • 49
    • 33646046156 scopus 로고    scopus 로고
    • Consensus review: a method of assessment of calcifications that appropriately undergo a six-month follow-up
    • Kuzmiak CM, Dancel R, Pisano E et al (2006) Consensus review: a method of assessment of calcifications that appropriately undergo a six-month follow-up. Acad Radiol 13(5): 621-629.
    • (2006) Acad Radiol , vol.13 , Issue.5 , pp. 621-629
    • Kuzmiak, C.M.1    Dancel, R.2    Pisano, E.3
  • 50
    • 62349100904 scopus 로고    scopus 로고
    • A time- and memory-efficient algorithm for automated segmentation of breast cancer nuclei
    • (in Korean)
    • Lee K, Street WN (2003) A time- and memory-efficient algorithm for automated segmentation of breast cancer nuclei. J Korea Inform Sci Soc 30(9-10): 973-982 (in Korean).
    • (2003) J Korea Inform Sci Soc , vol.30 , Issue.9-10 , pp. 973-982
    • Lee, K.1    Street, W.N.2
  • 51
    • 0035359279 scopus 로고    scopus 로고
    • An efficient fuzzy classifier with feature selection based on fuzzy entropy
    • Lee HM, Chen CM, Chen JM, Jou YL (2001) An efficient fuzzy classifier with feature selection based on fuzzy entropy. IEEE Trans Syst Man Cybern Part B 31(3): 426-432.
    • (2001) IEEE Trans Syst Man Cybern Part B , vol.31 , Issue.3 , pp. 426-432
    • Lee, H.M.1    Chen, C.M.2    Chen, J.M.3    Jou, Y.L.4
  • 53
    • 33646099818 scopus 로고    scopus 로고
    • FS_SFS: a novel feature selection method for support vector machines
    • Liu Y, Zheng YF (2006) FS_SFS: a novel feature selection method for support vector machines. Pattern Recogn 39(7): 1333-1345.
    • (2006) Pattern Recogn , vol.39 , Issue.7 , pp. 1333-1345
    • Liu, Y.1    Zheng, Y.F.2
  • 54
    • 0032730109 scopus 로고    scopus 로고
    • Artificial neural networks applied to survival prediction in breast cancer
    • Lundin M, Lundin J, Burke HB et al (1999) Artificial neural networks applied to survival prediction in breast cancer. Oncology 57(4): 281-286.
    • (1999) Oncology , vol.57 , Issue.4 , pp. 281-286
    • Lundin, M.1    Lundin, J.2    Burke, H.B.3
  • 55
    • 62349140853 scopus 로고    scopus 로고
    • Automated breast cancer diagnosis based on GVF-snake segmentation, wavelet features extraction and fuzzy classification
    • Malek J, Sebri A, Mabrouk S et al (2009) Automated breast cancer diagnosis based on GVF-snake segmentation, wavelet features extraction and fuzzy classification. Signal Process Syst 55(1-3): 49-66.
    • (2009) Signal Process Syst , vol.55 , Issue.1-3 , pp. 49-66
    • Malek, J.1    Sebri, A.2    Mabrouk, S.3
  • 56
    • 0016451032 scopus 로고
    • An experiment in linguistic synthesis with a fuzzy logic controller
    • Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man-Mach Stud 7(1): 1-13.
    • (1975) Int J Man-Mach Stud , vol.7 , Issue.1 , pp. 1-13
    • Mamdani, E.H.1    Assilian, S.2
  • 58
    • 0032924219 scopus 로고    scopus 로고
    • Reasoning with uncertainty in pathology: artificial neural networks and logistic regression as tools for prediction of lymph node status in breast cancer patients
    • Marchevsky AM, Shah S, Patel S (1999) Reasoning with uncertainty in pathology: artificial neural networks and logistic regression as tools for prediction of lymph node status in breast cancer patients. Mod Pathol 12(5): 505-513.
    • (1999) Mod Pathol , vol.12 , Issue.5 , pp. 505-513
    • Marchevsky, A.M.1    Shah, S.2    Patel, S.3
  • 59
    • 8244219678 scopus 로고    scopus 로고
    • Prognostic factors for metachronous contralateral breast cancer: a comparison of the linear Cox regression model and its artificial neural network extension
    • Mariani L, Coradini D, Biganzoli E et al (1997) Prognostic factors for metachronous contralateral breast cancer: a comparison of the linear Cox regression model and its artificial neural network extension. Breast Cancer Res Treat 44(2): 167-178.
    • (1997) Breast Cancer Res Treat , vol.44 , Issue.2 , pp. 167-178
    • Mariani, L.1    Coradini, D.2    Biganzoli, E.3
  • 60
    • 10244235420 scopus 로고    scopus 로고
    • Prediction of the axillary lymph node status in mammary cancer on the basis of clinicopathological data and flow cytometry
    • Mattfeldt T, Kestler HA, Sinn HP (2004) Prediction of the axillary lymph node status in mammary cancer on the basis of clinicopathological data and flow cytometry. Med Biol Eng Comput 42(6): 733-739.
    • (2004) Med Biol Eng Comput , vol.42 , Issue.6 , pp. 733-739
    • Mattfeldt, T.1    Kestler, H.A.2    Sinn, H.P.3
  • 61
    • 40649126091 scopus 로고    scopus 로고
    • Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance
    • Mazurowski MA, Habas PA, Zurada JM et al (2008) Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance. Neural Netw 21(2-3): 427-436.
    • (2008) Neural Netw , vol.21 , Issue.2-3 , pp. 427-436
    • Mazurowski, M.A.1    Habas, P.A.2    Zurada, J.M.3
  • 62
    • 12444337492 scopus 로고    scopus 로고
    • A prototype methodology combining surface-enhanced laser desorption/ionization protein chip technology and artificial neural network algorithms to predict the chemoresponsiveness of breast cancer cell lines exposed to Paclitaxel and Doxorubicin under in vitro conditions
    • Mian S, Ball G, Hornbuckle J et al (2003) A prototype methodology combining surface-enhanced laser desorption/ionization protein chip technology and artificial neural network algorithms to predict the chemoresponsiveness of breast cancer cell lines exposed to Paclitaxel and Doxorubicin under in vitro conditions. Proteomics 3(9): 1725-1737.
    • (2003) Proteomics , vol.3 , Issue.9 , pp. 1725-1737
    • Mian, S.1    Ball, G.2    Hornbuckle, J.3
  • 63
    • 0034187785 scopus 로고    scopus 로고
    • Neuro-fuzzy rule generation: survey in soft computing framework
    • Mitra S, Hayashi Y (2000) Neuro-fuzzy rule generation: survey in soft computing framework. IEEE Trans Neural Netw 11(3): 748-757.
    • (2000) IEEE Trans Neural Netw , vol.11 , Issue.3 , pp. 748-757
    • Mitra, S.1    Hayashi, Y.2
  • 64
    • 77958472400 scopus 로고    scopus 로고
    • Subclass fuzzy-SVM classifier as an efficient method to enhance the mass detection in mammograms
    • Moayedi F, Boostani R, Kazemi AR, Katebi S, Dashti E (2010) Subclass fuzzy-SVM classifier as an efficient method to enhance the mass detection in mammograms. Iran J Fuzzy Syst 7(1): 15-31.
    • (2010) Iran J Fuzzy Syst , vol.7 , Issue.1 , pp. 15-31
    • Moayedi, F.1    Boostani, R.2    Kazemi, A.R.3    Katebi, S.4    Dashti, E.5
  • 65
    • 0027205884 scopus 로고
    • A scaled conjugate gradient algorithm for fast supervised learning
    • Moller MF (1993) A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw 6: 525-533.
    • (1993) Neural Netw , vol.6 , pp. 525-533
    • Moller, M.F.1
  • 66
    • 17844381877 scopus 로고    scopus 로고
    • Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural
    • Mousa R, Munib Q, Moussa A (2005) Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural. Expert Syst Appl 28(4): 713-723.
    • (2005) Expert Syst Appl , vol.28 , Issue.4 , pp. 713-723
    • Mousa, R.1    Munib, Q.2    Moussa, A.3
  • 67
    • 0033084166 scopus 로고    scopus 로고
    • DNA ploidy and cell cycle distribution of breast cancer aspirate cells measured by image cytometry and analyzed by artificial neural networks for their prognostic significance
    • Naguib RN, Sakim HA, Lakshmi MS et al (1999) DNA ploidy and cell cycle distribution of breast cancer aspirate cells measured by image cytometry and analyzed by artificial neural networks for their prognostic significance. IEEE Trans Inf Technol Biomed 3(1): 61-69.
    • (1999) IEEE Trans Inf Technol Biomed , vol.3 , Issue.1 , pp. 61-69
    • Naguib, R.N.1    Sakim, H.A.2    Lakshmi, M.S.3
  • 68
    • 0030764424 scopus 로고    scopus 로고
    • Prediction of nodal metastasis and prognosis in breast cancer: a neural model
    • Naguib RN, Adams AE, Horne CH et al (1997) Prediction of nodal metastasis and prognosis in breast cancer: a neural model. Anticancer Res 17(4A): 2735-2741.
    • (1997) Anticancer Res , vol.17 , Issue.4 A , pp. 2735-2741
    • Naguib, R.N.1    Adams, A.E.2    Horne, C.H.3
  • 69
    • 0001623515 scopus 로고    scopus 로고
    • Neuro-fuzzy systems for function approximation
    • Nauck D, Kruse R (1999) Neuro-fuzzy systems for function approximation. Fuzzy Sets Syst 10(2): 261-271.
    • (1999) Fuzzy Sets Syst , vol.10 , Issue.2 , pp. 261-271
    • Nauck, D.1    Kruse, R.2
  • 70
    • 0037211870 scopus 로고    scopus 로고
    • Midpoint for fuzzy sets and their application in medicine
    • Nieto J, Torres A (2003) Midpoint for fuzzy sets and their application in medicine. Artif Intell Med 27(1): 321-355.
    • (2003) Artif Intell Med , vol.27 , Issue.1 , pp. 321-355
    • Nieto, J.1    Torres, A.2
  • 71
    • 82755190068 scopus 로고    scopus 로고
    • A comparative study on breast cancer prediction using RBF and MLP
    • Padmavati J (2011) A comparative study on breast cancer prediction using RBF and MLP. Int J Sci Eng Res 2(1): 1-5.
    • (2011) Int J Sci Eng Res , vol.2 , Issue.1 , pp. 1-5
    • Padmavati, J.1
  • 72
    • 0344466786 scopus 로고    scopus 로고
    • A fuzzy-genetic approach to breast cancer diagnosis
    • Pena-Reyes CA, Sipper M (1999) A fuzzy-genetic approach to breast cancer diagnosis. Artif Intell Med 17(2): 131-155.
    • (1999) Artif Intell Med , vol.17 , Issue.2 , pp. 131-155
    • Pena-Reyes, C.A.1    Sipper, M.2
  • 73
    • 33846446220 scopus 로고
    • Restart procedures for the conjugate gradient method
    • Powell M (1977) Restart procedures for the conjugate gradient method. Math Program 12(1): 241-254.
    • (1977) Math Program , vol.12 , Issue.1 , pp. 241-254
    • Powell, M.1
  • 74
    • 84860320195 scopus 로고    scopus 로고
    • Parallel approach for diagnosis of breast cancer using neural network technique
    • Rani KU (2010) Parallel approach for diagnosis of breast cancer using neural network technique. Int J Comput Appl 10(3): 1-5.
    • (2010) Int J Comput Appl , vol.10 , Issue.3 , pp. 1-5
    • Rani, K.U.1
  • 75
    • 1442350707 scopus 로고    scopus 로고
    • Non-linear survival analysis using neural networks
    • Ripley RM, Harris AL, Tarassenko L (2004) Non-linear survival analysis using neural networks. Stat Med 23(5): 825-842.
    • (2004) Stat Med , vol.23 , Issue.5 , pp. 825-842
    • Ripley, R.M.1    Harris, A.L.2    Tarassenko, L.3
  • 77
    • 0033052780 scopus 로고    scopus 로고
    • Use of artificial neural networks in modeling associations of discriminant factors: towards an intelligent selective breast cancer screening
    • Ronco AL (1999) Use of artificial neural networks in modeling associations of discriminant factors: towards an intelligent selective breast cancer screening. Artif Intell Med 16(3): 299-309.
    • (1999) Artif Intell Med , vol.16 , Issue.3 , pp. 299-309
    • Ronco, A.L.1
  • 80
    • 84885926165 scopus 로고    scopus 로고
    • Development of breast cancer diagnosis tool using hybrid magnetoacoustic method and artificial neural network
    • Salim MI, Ahmad AH, Ariffin I et al (2012) Development of breast cancer diagnosis tool using hybrid magnetoacoustic method and artificial neural network. Int J Biol Biomed Eng 6(1): 61-68.
    • (2012) Int J Biol Biomed Eng , vol.6 , Issue.1 , pp. 61-68
    • Salim, M.I.1    Ahmad, A.H.2    Ariffin, I.3
  • 81
    • 27144463192 scopus 로고    scopus 로고
    • On comparing classifiers: pitfalls to avoid and a recommended approach
    • Salzberg SL (1997) On comparing classifiers: pitfalls to avoid and a recommended approach. Data Min Knowl Disc 1(3): 317-327.
    • (1997) Data Min Knowl Disc , vol.1 , Issue.3 , pp. 317-327
    • Salzberg, S.L.1
  • 83
    • 73549102110 scopus 로고    scopus 로고
    • Automated breast cancer diagnosis based on GVF-snake segmentation, wavelet features extraction and neural network classification
    • Sebri A, Malek J, Tourki R (2007) Automated breast cancer diagnosis based on GVF-snake segmentation, wavelet features extraction and neural network classification. J Comput Sci 3(8): 600-607.
    • (2007) J Comput Sci , vol.3 , Issue.8 , pp. 600-607
    • Sebri, A.1    Malek, J.2    Tourki, R.3
  • 84
    • 0036254780 scopus 로고    scopus 로고
    • Assessment of nodal involvement and survival analysis in breast cancer patients using image cytometric data: statistical, neural network and fuzzy approaches
    • Seker H, Odetayo MO, Petrovic D et al (2002) Assessment of nodal involvement and survival analysis in breast cancer patients using image cytometric data: statistical, neural network and fuzzy approaches. Anticancer Res 22(1A): 433-438.
    • (2002) Anticancer Res , vol.22 , Issue.1 A , pp. 433-438
    • Seker, H.1    Odetayo, M.O.2    Petrovic, D.3
  • 85
    • 0022454805 scopus 로고
    • Breast calcifications: mammographic evaluation
    • Sickles EA (1986) Breast calcifications: mammographic evaluation. Radiology 160(2): 289-293.
    • (1986) Radiology , vol.160 , Issue.2 , pp. 289-293
    • Sickles, E.A.1
  • 86
    • 83755228864 scopus 로고    scopus 로고
    • Intuitionistic fuzzy C-means and decision tree approach for breast cancer detection and classification
    • Shanthi S, Bhaskaran VM (2011) Intuitionistic fuzzy C-means and decision tree approach for breast cancer detection and classification. Eur J Sci Res 66(3): 345-351.
    • (2011) Eur J Sci Res , vol.66 , Issue.3 , pp. 345-351
    • Shanthi, S.1    Bhaskaran, V.M.2
  • 87
    • 17844395370 scopus 로고    scopus 로고
    • Detection, synthesis and compression in mammographic image analysis using a hierarchical image probability model
    • Spence D, Parra L, Sajda P (2001) Detection, synthesis and compression in mammographic image analysis using a hierarchical image probability model. Artif Intell Med 25(31): 365-371.
    • (2001) Artif Intell Med , vol.25 , Issue.31 , pp. 365-371
    • Spence, D.1    Parra, L.2    Sajda, P.3
  • 88
    • 62349137293 scopus 로고
    • Toward automated cancer diagnosis: an interactive system for cell feature extraction
    • University of Wisconsin, Madison, WI
    • Street WN (1991) Toward automated cancer diagnosis: an interactive system for cell feature extraction. Technical Report 1052, Computer Sciences Department, University of Wisconsin, Madison, WI.
    • (1991) Technical Report 1052, Computer Sciences Department
    • Street, W.N.1
  • 90
    • 0000425261 scopus 로고    scopus 로고
    • Xcyt: A system for remote cytological diagnosis and prognosis of breast cancer
    • L. C. Jain (Ed.), Singapore: World Scientific Publishing
    • Street WN (2000) Xcyt: A system for remote cytological diagnosis and prognosis of breast cancer. In: Jain LC (ed) Soft computing techniques in breast cancer prognosis and diagnosis. World Scientific Publishing, Singapore, pp 297-322.
    • (2000) Soft Computing Techniques in Breast Cancer Prognosis and Diagnosis , pp. 297-322
    • Street, W.N.1
  • 94
    • 0021892282 scopus 로고
    • Fuzzy identification of systems and its applications to modeling and control
    • Takagi T, Sugeno M (1985) Fuzzy identification of systems and its applications to modeling and control. IEEE Trans Syst Man Cybern 15(1): 116-132.
    • (1985) IEEE Trans Syst Man Cybern , vol.15 , Issue.1 , pp. 116-132
    • Takagi, T.1    Sugeno, M.2
  • 96
    • 0035006815 scopus 로고    scopus 로고
    • A neural network approach to breast cancer diagnosis as a constraint satisfaction problem
    • Tourassi GD, Markey MK, Lo JY, Floyd CE (2001) A neural network approach to breast cancer diagnosis as a constraint satisfaction problem. Med Phys 28(5): 804-811.
    • (2001) Med Phys , vol.28 , Issue.5 , pp. 804-811
    • Tourassi, G.D.1    Markey, M.K.2    Lo, J.Y.3    Floyd, C.E.4
  • 97
    • 0037387684 scopus 로고    scopus 로고
    • OFFSS: optimal fuzzy-valued feature subset selection
    • Tsang ECC, Yeung DS, Wang XZ (2003) OFFSS: optimal fuzzy-valued feature subset selection. IEEE Trans Fuzzy Syst 11(2): 202-213.
    • (2003) IEEE Trans Fuzzy Syst , vol.11 , Issue.2 , pp. 202-213
    • Tsang, E.C.C.1    Yeung, D.S.2    Wang, X.Z.3
  • 98
    • 70449673352 scopus 로고    scopus 로고
    • Adaptive neuro-fuzzy inference systems for automatic detection of breast cancer
    • Übeyli ED (2009) Adaptive neuro-fuzzy inference systems for automatic detection of breast cancer. J Med Syst 33(5): 353-358.
    • (2009) J Med Syst , vol.33 , Issue.5 , pp. 353-358
    • Übeyli, E.D.1
  • 99
    • 34250666040 scopus 로고    scopus 로고
    • UCI, Accessed 23 Oct 2012
    • UCI (2012) Machine Learning Repository. http://archive. ics. uci. edu/ml/index. html. Accessed 23 Oct 2012.
    • (2012) Machine Learning Repository
  • 100
    • 0035263429 scopus 로고    scopus 로고
    • A computer-aided diagnosis system for digital mammograms based on fuzzy-neural and feature extraction techniques
    • Verma K, Zakos J (2001) A computer-aided diagnosis system for digital mammograms based on fuzzy-neural and feature extraction techniques. IEEE Trans Inf Technol Biomed 5(1): 46-54.
    • (2001) IEEE Trans Inf Technol Biomed , vol.5 , Issue.1 , pp. 46-54
    • Verma, K.1    Zakos, J.2
  • 102
    • 0036902547 scopus 로고    scopus 로고
    • Self-adaptive neuron-fuzzy inference systems for classification applications
    • Wang JS, Lee GCS (2002) Self-adaptive neuron-fuzzy inference systems for classification applications. IEEE Trans Fuzzy Syst 10(6): 790-802.
    • (2002) IEEE Trans Fuzzy Syst , vol.10 , Issue.6 , pp. 790-802
    • Wang, J.S.1    Lee, G.C.S.2
  • 103
    • 0036858715 scopus 로고    scopus 로고
    • Computer-generated nuclear features compared to axillary lymph node status and tumor size as indicators of breast cancer survival
    • Wolberg WH, Street WN (2002) Computer-generated nuclear features compared to axillary lymph node status and tumor size as indicators of breast cancer survival. Human Pathol 33(11): 1086-1091.
    • (2002) Human Pathol , vol.33 , Issue.11 , pp. 1086-1091
    • Wolberg, W.H.1    Street, W.N.2
  • 104
    • 0025651706 scopus 로고
    • Multisurface method of pattern separation for medical diagnosis applied to breast cytology
    • Wolberg WH, Mangasarian OL (1990) Multisurface method of pattern separation for medical diagnosis applied to breast cytology. Proc Natl Acad Sci USA 87: 9193-9196.
    • (1990) Proc Natl Acad Sci USA , vol.87 , pp. 9193-9196
    • Wolberg, W.H.1    Mangasarian, O.L.2
  • 107
    • 34248666540 scopus 로고
    • Fuzzy sets
    • Zadeh LA (1965) Fuzzy sets. Inform Cont 8(3): 338-353.
    • (1965) Inform Cont , vol.8 , Issue.3 , pp. 338-353
    • Zadeh, L.A.1
  • 108
    • 49949129142 scopus 로고
    • Fuzzy algorithm
    • Zadeh LA (1968) Fuzzy algorithm. Inf Cont 12(2): 94-102.
    • (1968) Inf Cont , vol.12 , Issue.2 , pp. 94-102
    • Zadeh, L.A.1
  • 109
    • 0015558134 scopus 로고
    • Outline of a new approach to the analysis of complex system and decision processes
    • Zadeh LA (1973) Outline of a new approach to the analysis of complex system and decision processes. IEEE Trans Syst Man Cyber 3(1): 28-44.
    • (1973) IEEE Trans Syst Man Cyber , vol.3 , Issue.1 , pp. 28-44
    • Zadeh, L.A.1
  • 110
    • 0020834371 scopus 로고
    • Commonsense knowledge representation based on fuzzy logic
    • Zadeh LA (1983) Commonsense knowledge representation based on fuzzy logic. IEEE Comput 16(10): 61-65.
    • (1983) IEEE Comput , vol.16 , Issue.10 , pp. 61-65
    • Zadeh, L.A.1
  • 111
    • 35148900657 scopus 로고
    • Fuzzy logic
    • Zadeh LA (1983) Fuzzy logic. IEEE Comput 1(4): 83-93.
    • (1983) IEEE Comput , vol.1 , Issue.4 , pp. 83-93
    • Zadeh, L.A.1


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