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Volumn 7, Issue 1, 2014, Pages

Fuzzy C-means in finding subtypes of cancers in cancer database

Author keywords

Cancer database; Entropy terms; Fuzzy C Means; Kernel induced distance

Indexed keywords

CLUSTER ANALYSIS; DATABASE SYSTEMS; ENTROPY; FUZZY SYSTEMS;

EID: 84896947358     PISSN: 17935458     EISSN: 17937205     Source Type: Journal    
DOI: 10.1142/S1793545814500187     Document Type: Article
Times cited : (4)

References (51)
  • 1
    • 77954143943 scopus 로고    scopus 로고
    • DNA hypermethylation of tumors from non-small cell lung cancer (NSCLC) patients is associated with gender and histologic type
    • Hawes et al., "DNA hypermethylation of tumors from non-small cell lung cancer (NSCLC) patients is associated with gender and histologic type," Lung Cancer 69, 172-179 (2010).
    • (2010) Lung Cancer , vol.69 , pp. 172-179
    • Hawes1
  • 3
    • 84897016284 scopus 로고    scopus 로고
    • Breast cancer facts and ̄gures 2003-2004
    • J. Calle, "Breast cancer facts and ̄gures 2003-2004," American Cancer Society, 1-27 (2004).
    • (2004) American Cancer Society , pp. 1-27
    • Calle, J.1
  • 4
    • 84896949953 scopus 로고    scopus 로고
    • National Cancer Control Programme: Current status and strategies 50 years of cancer control in India
    • Y. N. Rao, S. Gupta, S. P. Agarwal, "National Cancer Control Programme: Current status and strategies, 50 years of cancer control in India," NCD Section, Director General of Health (2003).
    • (2003) NCD Section Director General of Health
    • Rao, Y.N.1    Gupta, S.2    Agarwal, S.P.3
  • 5
    • 79952449647 scopus 로고    scopus 로고
    • A support vector machine classīer with rough set-based feature selection for breast cancer diagnosis
    • H.-L. Chen, B. Yang, J. Liu, D.-Y. Liu, "A support vector machine classīer with rough set-based feature selection for breast cancer diagnosis," Expert Syst. Appl. 38, 9014-9022 (2011).
    • (2011) Expert Syst. Appl. , vol.38 , pp. 9014-9022
    • Chen, H.-L.1    Yang, B.2    Liu, J.3    Liu, D.-Y.4
  • 6
    • 84865136885 scopus 로고    scopus 로고
    • Systematic analysis of in vitro chemosensitivity and mib-1 expression in molecular breast cancer subtypes
    • C. Liedtke et al., "Systematic analysis of in vitro chemosensitivity and mib-1 expression in molecular breast cancer subtypes," Eur. J. Cancer 48(13), 2066-2074 (2012).
    • (2012) Eur. J. Cancer , vol.48 , Issue.13 , pp. 2066-2074
    • Liedtke, C.1
  • 7
    • 84877142910 scopus 로고    scopus 로고
    • Association between common risk factors and molecular subtypes in breast cancer patients
    • F. P. Turkoz et al., "Association between common risk factors and molecular subtypes in breast cancer patients," Breast J. 22(3), 344-350 (2013).
    • (2013) Breast J. , vol.22 , Issue.3 , pp. 344-350
    • Turkoz, F.P.1
  • 8
    • 78650684673 scopus 로고    scopus 로고
    • Extended Gaussian kernel version of fuzzy c-means in the problem of data analyzing
    • Ramathilagam et al., "Extended Gaussian kernel version of fuzzy c-means in the problem of data analyzing," Expert Syst. Appl. 38(4), 3793-3805 (2011).
    • (2011) Expert Syst. Appl. , vol.38 , Issue.4 , pp. 3793-3805
    • Ramathilagam1
  • 9
    • 84883314367 scopus 로고    scopus 로고
    • Computer-aided diagnosis of breast cancer based on ̄ne needle biopsy microscopic images
    • M. Kowal et al., "Computer-aided diagnosis of breast cancer based on ̄ne needle biopsy microscopic images," Comput. Biol. Med. 43(10), 1563-1572 (2013).
    • (2013) Comput. Biol. Med. , vol.43 , Issue.10 , pp. 1563-1572
    • Kowal, M.1
  • 11
    • 0019280022 scopus 로고
    • Clustering methodology in exploratory data analysis
    • M. C. Yovits, Ed. Academic Press, New York
    • R. C. Dubes, A. K. Jain, Clustering methodology in Exploratory Data Analysis, Advances in Computers, M. C. Yovits, Ed., pp. 113-225 (Academic Press, New York, 1980).
    • (1980) Advances in Computers , pp. 113-225
    • Dubes, R.C.1    Jain, A.K.2
  • 12
    • 43149092856 scopus 로고    scopus 로고
    • A novel Fuzzy Cmeans clustering algorithm for image thresholding\
    • Y. Yong, Z. Chongxun, L. Pan, "A novel Fuzzy Cmeans clustering algorithm for image thresholding," Meas. Sci. Rev. 4, 11-19 (2004).
    • (2004) Meas. Sci. Rev. , vol.4
    • Yong, Y.1    Chongxun, Z.2    Pan, L.3
  • 13
    • 34248666540 scopus 로고
    • Fuzzy sets
    • L. A. Zadeh, "Fuzzy sets," Inf. Control 8, 338-353 (1965).
    • (1965) Inf. Control , vol.8 , pp. 338-353
    • Zadeh, L.A.1
  • 14
    • 0015644825 scopus 로고
    • A fuzzy relative of the Isodata process and its use in detecting compact, well-separated clusters
    • J. Dunn, "A fuzzy relative of the Isodata process and its use in detecting compact, well-separated clusters," J. Cybernetics 3(3), 32-57 (1973).
    • (1973) J. Cybernetics , vol.3 , Issue.3 , pp. 32-57
    • Dunn, J.1
  • 15
    • 84896979645 scopus 로고    scopus 로고
    • Clustering problem using Fuzzy C-means algorithms and unsupervised neural networks
    • J.-S. Lin, "Clustering problem using Fuzzy C-means algorithms and unsupervised neural networks," Neuro-Fuzzy Pattern Recogn. 41, 75-99 (2000).
    • (2000) Neuro-Fuzzy Pattern Recogn , vol.41 , pp. 75-99
    • Lin, J.-S.1
  • 17
    • 84861401213 scopus 로고    scopus 로고
    • Intuitionistic Fuzzy C means clustering in medical image segmentation
    • Chaira et al., "Intuitionistic Fuzzy C means clustering in medical image segmentation," Adv. Pattern Recogn. 1, 226-230 (2007).
    • (2007) Adv. Pattern Recogn. , vol.1 , pp. 226-230
    • Chaira1
  • 18
    • 51449113654 scopus 로고    scopus 로고
    • Fuzzy C-means algorithm with local thresholding for gray-scale images
    • H. P. Ng et al., "Fuzzy C-means algorithm with local thresholding for gray-scale images," Int. J. Artif. Intell. Tools 17(04), 765-775 (2008).
    • (2008) Int. J. Artif. Intell. Tools , vol.17 , Issue.4 , pp. 765-775
    • Ng, H.P.1
  • 19
    • 29344464574 scopus 로고    scopus 로고
    • A novel Fuzzy C-means algorithm and its application
    • K. Yuan et al., "A novel Fuzzy C-means algorithm and its application," Int. J. Pattern Recogn. Artif. Intell. 19(08), 1059-1066 (2005).
    • (2005) Int. J. Pattern Recogn. Artif. Intell. , vol.19 , Issue.8 , pp. 1059-1066
    • Yuan, K.1
  • 20
    • 81455142100 scopus 로고    scopus 로고
    • UA Novel video steganography based on non-uniform rectangularpartition
    • CSE/I-SPAN/IUCC 2011 doi: 10.1109/CSE.2011.24
    • S. D. Hu, K. Tak, U. \A Novel video steganography based on non-uniform rectangularpartition," IEEEInt. Conf. Computational Science and Engineering CSE/I-SPAN/IUCC 2011, doi: 10.1109/CSE.2011.24.
    • IEEEInt. Conf. Computational Science and Engineering
    • Hu, S.D.1    Tak, K.2
  • 21
    • 84885053531 scopus 로고    scopus 로고
    • Brain tissue classīcation based on DTI using an improved Fuzzy C-means algorithm with spatial constraints
    • Y. Wen, "Brain tissue classīcation based on DTI using an improved Fuzzy C-means algorithm with spatial constraints," Magn. Reson. Imaging 31(9), 1623-1630 (2013).
    • (2013) Magn. Reson. Imaging , vol.31 , Issue.9 , pp. 1623-1630
    • Wen, Y.1
  • 22
    • 84896955585 scopus 로고    scopus 로고
    • Fast Fuzzy c-means clustering algorithm with spatial constraints for image segmentation
    • Springer
    • Y. Li et al., "Fast Fuzzy c-means clustering algorithm with spatial constraints for image segmentation," Advances in Neural Network Research and Applications, Springer (2010).
    • (2010) Advances in Neural Network Research and Applications
    • Li, Y.1
  • 23
    • 84863207488 scopus 로고    scopus 로고
    • A biomedical decision support system using LS-SVM classīer with an e±cient and new parameter regularization procedure for diagnosis of heart valve diseases
    • doi: 10.1007/s10916-010-9500-5
    • E. Çomak, "A biomedical decision support system using LS-SVM classīer with an e±cient and new parameter regularization procedure for diagnosis of heart valve diseases," J. Med. Syst. 36, 549-556 (2012), doi: 10.1007/s10916-010-9500-5.
    • (2012) J. Med. Syst. , vol.36 , pp. 549-556
    • Çomak, E.1
  • 24
    • 84885675910 scopus 로고    scopus 로고
    • A novel ant-based clustering algorithm using Renyi entropy
    • L. Zhang et al., "A novel ant-based clustering algorithm using Renyi entropy," Appl. Soft Comput. 13, 2643-2657 (2013).
    • (2013) Appl. Soft Comput. , vol.13 , pp. 2643-2657
    • Zhang, L.1
  • 25
    • 79957516063 scopus 로고    scopus 로고
    • An initialization method to simultaneously ̄nd initial cluster centers and the number of clusters for clustering categorical data
    • L. Bai et al., "An initialization method to simultaneously ̄nd initial cluster centers and the number of clusters for clustering categorical data," Knowledge-Based Syst. 24, 785-795 (2011).
    • (2011) Knowledge-Based Syst , vol.24 , pp. 785-795
    • Bai, L.1
  • 26
    • 23844528211 scopus 로고    scopus 로고
    • Cluster center initialization algorithm for K-means clustering
    • S. Shehroz et al., "Cluster center initialization algorithm for K-means clustering," Pattern Recognit. Lett. 25, 1293-1302 (2004).
    • (2004) Pattern Recognit. Lett. , vol.25 , pp. 1293-1302
    • Shehroz, S.1
  • 28
    • 45849113230 scopus 로고    scopus 로고
    • A Gaussian kernel-based fuzzy cmeans algorithm with a spatial bias correction
    • M.-S. Yang et al., "A Gaussian kernel-based fuzzy cmeans algorithm with a spatial bias correction," Pattern Recogn. Lett. 29, 1713-1725 (2008).
    • (2008) Pattern Recogn. Lett. , vol.29 , pp. 1713-1725
    • Yang, M.-S.1
  • 29
    • 84896917595 scopus 로고    scopus 로고
    • Robust adaptive threshold algorithm based on Kernel Fuzzy clustering on image segmentation
    • N. Meghanathan et al. Ed. SIP, JSE-2012, CS & IT 04 doi: 10.5121/csit.2012.2109
    • Saikumar et al., "Robust adaptive threshold algorithm based on Kernel Fuzzy clustering on image segmentation," The First Int. Conf. Information Technology Convergence and Services, ITCS 2012, N. Meghanathan et al. Ed. SIP, JSE-2012, CS & IT 04, pp. 99-103 (2012), doi: 10.5121/csit.2012.2109.
    • (2012) The First Int. Conf. Information Technology Convergence and Services ITCS 2012 , pp. 99-103
    • Saikumar1
  • 30
    • 3543098627 scopus 로고    scopus 로고
    • Robust image segmentation using FCM with spatial constraints based on new Kernelinduced distance measure
    • S.Chen, D.Zhang, "Robust image segmentation using FCM with spatial constraints based on new Kernelinduced distance measure," IEEE Trans. Syst. Man Cybern. B Cybern. 34(4), 1907-1916 (2004).
    • (2004) IEEE Trans. Syst. Man Cybern. B Cybern , vol.34 , Issue.4 , pp. 1907-1916
    • Chen, S.1    Zhang, D.2
  • 31
    • 0036565280 scopus 로고    scopus 로고
    • Mercer-based clustering in feature space
    • M. Girolami, "Mercer-based clustering in feature space," IEEE Trans. Neural Netw. 13(3), 780-784 (2002).
    • (2002) IEEE Trans. Neural Netw. , vol.13 , Issue.3 , pp. 780-784
    • Girolami, M.1
  • 32
    • 46749142532 scopus 로고    scopus 로고
    • ClValid, an R package for cluster validation
    • G. N. Brock, V. Pihur, S. Datta, S. Datta, "clValid, an R package for cluster validation," J. Stat. Software 25(4), 1-22 (2008).
    • (2008) J. Stat. Software , vol.25 , Issue.4 , pp. 1-22
    • Brock, G.N.1    Pihur, V.2    Datta, S.3    Datta, S.4
  • 33
    • 0023453329 scopus 로고
    • Silhouettes: A Graphical aid to the interpretation and validation of cluster analysis
    • P. J. Rousseeuw, "Silhouettes: A Graphical aid to the interpretation and validation of cluster analysis," J. Comput. Appl. Math. 20, 53-65 (1987).
    • (1987) J. Comput. Appl. Math. , vol.20 , pp. 53-65
    • Rousseeuw, P.J.1
  • 35
    • 84869022987 scopus 로고    scopus 로고
    • A knowledge-driven biclustering method for mining noisy datasets
    • Springer
    • K. Mouhoubi et al., A knowledge-driven biclustering method for mining noisy datasets, Neural Information Processing, Lecture Notes in Computer Science, Vol. 7665, pp. 585-593, Springer (2010).
    • (2010) Neural Information Processing, Lecture Notes in Computer Science , vol.7665 , pp. 585-593
    • Mouhoubi, K.1
  • 36
    • 80052952912 scopus 로고    scopus 로고
    • An E±cient successive iteration partial cluster algorithm for large datasets, Fuzzy information and engineering 2010
    • D. Hou et al., "An E±cient successive iteration partial cluster algorithm for large datasets, Fuzzy information and engineering 2010," Adv. Intell. Soft Comput. 78, 557-562 (2010).
    • (2010) Adv. Intell. Soft Comput , vol.78 , pp. 557-562
    • Hou, D.1
  • 37
    • 84897015582 scopus 로고    scopus 로고
    • Empirical comparison of sampling strategies for classīcation
    • K. Das et. al., "Empirical comparison of sampling strategies for classīcation," Procedia Eng. 38, 1072-1076 (2012).
    • (2012) Procedia Eng. , vol.38 , pp. 1072-1076
    • Das, K.1
  • 38
    • 0036735386 scopus 로고    scopus 로고
    • Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and Mesothelioma
    • G. J. Gordon et al., "Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and Mesothelioma," Cancer Res. 62, 4963-4967 (2002).
    • (2002) Cancer Res. , vol.62 , pp. 4963-4967
    • Gordon, G.J.1
  • 40
    • 0038537359 scopus 로고    scopus 로고
    • Speeding Up Fuzzy Clustering with Neural Network Techniques
    • FUZZ-IEEE'03, St. Louis, MO, USA, IEEE Press, Piscataway, NJ, USA
    • C. Borgelt, R. Kruse, Speeding up Fuzzy clustering with neural network techniques, Proc. 12th IEEE Int. Conf. Fuzzy Systems, FUZZ-IEEE'03, St. Louis, MO, USA, IEEE Press, Piscataway, NJ, USA (2003).
    • (2003) Proc. 12th IEEE Int. Conf. Fuzzy Systems
    • Borgelt, C.1    Kruse, R.2
  • 41
    • 0001849156 scopus 로고    scopus 로고
    • Multicategory classīcation by support vector machines
    • E. J. Bredenstenier, K. P. Bennett, "Multicategory classīcation by support vector machines," Comput. Optim. Appl. 12, 53-79 (1999).
    • (1999) Comput. Optim. Appl. , vol.12 , pp. 53-79
    • Bredenstenier, E.J.1    Bennett, K.P.2
  • 42
    • 26444454606 scopus 로고    scopus 로고
    • Feature selection for unsupervised learning
    • J. G. Dy, C. E. Brodley, "Feature selection for unsupervised learning," J. Mach. Learn. Res. 5, 845-889 (2004).
    • (2004) J. Mach. Learn. Res. , vol.5 , pp. 845-889
    • Dy, J.G.1    Brodley, C.E.2
  • 43
    • 0842300534 scopus 로고    scopus 로고
    • Clustering incomplete data using Kernel-based Fuzzy C-means algorithm
    • D.-Q. Zhang, S.-C. Chen, "Clustering incomplete data using Kernel-based Fuzzy C-means algorithm," Neural Process. Lett. 18, 155-162 (2003).
    • (2003) Neural Process. Lett. , vol.18 , pp. 155-162
    • Zhang, D.-Q.1    Chen, S.-C.2
  • 44
    • 34247170075 scopus 로고    scopus 로고
    • A robust deterministic annealing algorithm for data clustering
    • X.-L. Yang, Q. Song, Y.-L. Wu, "A robust deterministic annealing algorithm for data clustering," Data Knowl. Eng. 62, 84-100 (2007).
    • (2007) Data Knowl. Eng. , vol.62 , pp. 84-100
    • Yang, X.-L.1    Song, Q.2    Wu, Y.-L.3
  • 45
    • 84859451115 scopus 로고    scopus 로고
    • Whole-brain, timelocked activation with simple tasks revealed using massive averaging and model-free analysis
    • J. Gonzalez-Castillo et al., "Whole-brain, timelocked activation with simple tasks revealed using massive averaging and model-free analysis," Proc. Natl. Acad. Sci. USA 109(14), 5487-5492 (2012).
    • (2012) Proc. Natl. Acad. Sci. USA , vol.109 , Issue.14 , pp. 5487-5492
    • Gonzalez-Castillo, J.1
  • 49
    • 70349811563 scopus 로고    scopus 로고
    • Time series analysis with multiple resolutions
    • doi: 10.1016/j.is.2009.03.006
    • Q. Wang, V. Megalooikonomou, C. Faloutsos, "Time series analysis with multiple resolutions," Inf. Syst. doi: 10.1016/j.is.2009.03.006.
    • Inf. Syst
    • Wang, Q.1    Megalooikonomou, V.2    Faloutsos, C.3
  • 50
    • 35748941262 scopus 로고    scopus 로고
    • A dimensionality reduction technique for e±cient time series similarity analysis
    • Q. Wang, V. Megalooikonomou, "A dimensionality reduction technique for e±cient time series similarity analysis," Inf. Syst. 33, 115-132 (2008).
    • (2008) Inf. Syst. , vol.33 , pp. 115-132
    • Wang, Q.1    Megalooikonomou, V.2
  • 51
    • 2442512707 scopus 로고    scopus 로고
    • Time-series similarity queries employing a feature-based approach
    • 27-29 August 1999, Ioannina, Greece
    • R. J. Alcock, Y. Manolopoulos, "Time-series similarity queries employing a feature-based approach," 7th Hellenic Conf. Informatics, 27-29 August, 1999, Ioannina, Greece, 1999.
    • (1999) 7th Hellenic Conf. Informatics
    • Alcock, R.J.1    Manolopoulos, Y.2


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