{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:01:46Z","timestamp":1758268906030,"version":"3.37.3"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T00:00:00Z","timestamp":1567468800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T00:00:00Z","timestamp":1567468800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["106-2221-E-155-MY3"],"award-info":[{"award-number":["106-2221-E-155-MY3"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Fuzzy Syst."],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1007\/s40815-019-00730-x","type":"journal-article","created":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T18:49:05Z","timestamp":1567536545000},"page":"2258-2269","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A K-means Interval Type-2 Fuzzy Neural Network for Medical Diagnosis"],"prefix":"10.1007","volume":"21","author":[{"given":"Tien-Loc","family":"Le","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tuan-Tu","family":"Huynh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lo-Yi","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chih-Min","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Chao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,9,3]]},"reference":[{"issue":"804","key":"730_CR1","first-page":"801","volume":"1","author":"H Steinhaus","year":"1956","unstructured":"Steinhaus, H.: Sur la division des corp materiels en parties. Bull. Acad. Polonaise Sci. 1(804), 801 (1956)","journal-title":"Bull. Acad. Polonaise Sci."},{"issue":"2","key":"730_CR2","first-page":"271","volume":"6","author":"J Xie","year":"2011","unstructured":"Xie, J., Jiang, S., Xie, W., Gao, X.: An efficient global K-means clustering algorithm. J. Comput. Phys. 6(2), 271\u2013279 (2011)","journal-title":"J. Comput. Phys."},{"issue":"3","key":"730_CR3","first-page":"1","volume":"1","author":"P Vora","year":"2013","unstructured":"Vora, P., Oza, B.: A survey on K-mean clustering and particle swarm optimization. Int. J. Sci. Mod. Eng. 1(3), 1\u201314 (2013)","journal-title":"Int. J. Sci. Mod. Eng."},{"issue":"3","key":"730_CR4","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1007\/s40430-016-0559-x","volume":"39","author":"M Yunoh","year":"2017","unstructured":"Yunoh, M., Abdullah, S., Saad, M., Nopiah, Z., Nuawi, M.: K-means clustering analysis and artificial neural network classification of fatigue strain signals. J. Brazilian Soc. Mech. Sci. Eng. 39(3), 757\u2013764 (2017)","journal-title":"J. Brazilian Soc. Mech. Sci. Eng."},{"key":"730_CR5","first-page":"105","volume":"12","author":"K Singh","year":"2011","unstructured":"Singh, K., Malik, D., Sharma, N.: Evolving limitations in K-means algorithm in data mining and their removal. Int. J. Comput. Eng. Manag. 12, 105\u2013109 (2011)","journal-title":"Int. J. Comput. Eng. Manag."},{"key":"730_CR6","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/978-3-319-29052-2_5","volume-title":"Advances in Acoustic Emission Technology","author":"P Jiang","year":"2017","unstructured":"Jiang, P., Zhang, L., Li, W., Wang, X.: Pattern recognition for acoustic emission signals of offshore platform T-tube damage based on K-means clustering. Advances in Acoustic Emission Technology, pp. 53\u201361. Springer, Berlin (2017)"},{"key":"730_CR7","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1016\/j.measurement.2018.04.002","volume":"123","author":"SA Tuncer","year":"2018","unstructured":"Tuncer, S.A., Alkan, A.: A decision support system for detection of the renal cell cancer in the kidney. Measurement 123, 298\u2013303 (2018)","journal-title":"Measurement"},{"key":"730_CR8","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1016\/j.patrec.2017.03.008","volume":"90","author":"G Gan","year":"2017","unstructured":"Gan, G., Ng, M.K.-P.: K-means clustering with outlier removal. Pattern Recogn. Lett. 90, 8\u201314 (2017)","journal-title":"Pattern Recogn. Lett."},{"issue":"3","key":"730_CR9","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1016\/S0019-9958(65)90241-X","volume":"8","author":"LA Zadeh","year":"1965","unstructured":"Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338\u2013353 (1965)","journal-title":"Inf. Control"},{"issue":"3","key":"730_CR10","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/0020-0255(75)90036-5","volume":"8","author":"LA Zadeh","year":"1975","unstructured":"Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning\u2014I. Inf. Sci. 8(3), 199\u2013249 (1975)","journal-title":"Inf. Sci."},{"issue":"5","key":"730_CR11","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1109\/91.873577","volume":"8","author":"Q Liang","year":"2000","unstructured":"Liang, Q., Mendel, J.M.: Interval type-2 fuzzy logic systems: theory and design. IEEE Trans. Fuzzy Syst. 8(5), 535\u2013550 (2000)","journal-title":"IEEE Trans. Fuzzy Syst."},{"issue":"4","key":"730_CR12","doi-asserted-by":"publisher","first-page":"2396","DOI":"10.1109\/TFUZZ.2017.2775599","volume":"26","author":"I Eyoh","year":"2017","unstructured":"Eyoh, I., John, R., De Maere, G.: Interval type-2 intuitionistic fuzzy logic for regression problems. IEEE Trans. Fuzzy Syst. 26(4), 2396\u20132408 (2017)","journal-title":"IEEE Trans. Fuzzy Syst."},{"issue":"1","key":"730_CR13","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1007\/s11071-014-1683-8","volume":"79","author":"MM Zirkohi","year":"2015","unstructured":"Zirkohi, M.M., Lin, T.-C.: Interval type-2 fuzzy-neural network indirect adaptive sliding mode control for an active suspension system. Nonlinear Dyn. 79(1), 513\u2013526 (2015)","journal-title":"Nonlinear Dyn."},{"key":"730_CR14","doi-asserted-by":"publisher","first-page":"2239","DOI":"10.1016\/j.neucom.2017.11.009","volume":"275","author":"C-M Lin","year":"2018","unstructured":"Lin, C.-M., Le, T.-L., Huynh, T.-T.: Self-evolving function-link interval type-2 fuzzy neural network for nonlinear system identification and control. Neurocomputing 275, 2239\u20132250 (2018)","journal-title":"Neurocomputing"},{"issue":"5","key":"730_CR15","doi-asserted-by":"publisher","first-page":"1362","DOI":"10.1007\/s40815-017-0301-6","volume":"19","author":"C-M Lin","year":"2017","unstructured":"Lin, C.-M., Le, T.-L.: PSO-self-organizing interval type-2 fuzzy neural network for antilock braking systems. Int. J. Fuzzy Syst. 19(5), 1362\u20131374 (2017)","journal-title":"Int. J. Fuzzy Syst."},{"issue":"1","key":"730_CR16","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1109\/TFUZZ.2017.2648855","volume":"26","author":"H Li","year":"2018","unstructured":"Li, H., Wang, J., Wu, L., Lam, H.-K., Gao, Y.: Optimal guaranteed cost sliding-mode control of interval type-2 fuzzy time-delay systems. IEEE Trans. Fuzzy Syst. 26(1), 246\u2013257 (2018)","journal-title":"IEEE Trans. Fuzzy Syst."},{"issue":"4","key":"730_CR17","first-page":"39","volume":"13","author":"J-S Guan","year":"2016","unstructured":"Guan, J.-S., Lin, L.-Y., Ji, G.L., Lin, C.-M., Le, T.-L., Rudas, I.J.: Breast tumor computer-aided diagnosis using self-validating cerebellar model neural networks. Acta Polytech. Hung. 13(4), 39\u201352 (2016)","journal-title":"Acta Polytech. Hung."},{"issue":"2","key":"730_CR18","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1007\/s40815-017-0326-x","volume":"20","author":"Q Zhou","year":"2018","unstructured":"Zhou, Q., Chao, F., Lin, C.-M.: A functional-link-based fuzzy brain emotional learning network for breast tumor classification and chaotic system synchronization. Int. J. Fuzzy Syst. 20(2), 349\u2013365 (2018)","journal-title":"Int. J. Fuzzy Syst."},{"issue":"10","key":"730_CR19","first-page":"1","volume":"29","author":"AK Dwivedi","year":"2016","unstructured":"Dwivedi, A.K.: Performance evaluation of different machine learning techniques for prediction of heart disease. Neural Comput. Appl. 29(10), 1\u20139 (2016)","journal-title":"Neural Comput. Appl."},{"key":"730_CR20","first-page":"1","volume":"2017","author":"X Liu","year":"2017","unstructured":"Liu, X., Wang, X., Su, Q., Zhang, M., Zhu, Y., Wang, Q., Wang, Q.: A hybrid classification system for heart disease diagnosis based on the RFRS method. Comput. Math. Methods Med. 2017, 1\u201311 (2017)","journal-title":"Comput. Math. Methods Med."},{"issue":"6","key":"730_CR21","doi-asserted-by":"publisher","first-page":"820","DOI":"10.1007\/s40846-016-0191-3","volume":"36","author":"E Y\u0131lmaz","year":"2016","unstructured":"Y\u0131lmaz, E.: Fetal state assessment from cardiotocogram data using artificial neural networks. J. Med. Biol. Eng. 36(6), 820\u2013832 (2016)","journal-title":"J. Med. Biol. Eng."},{"issue":"9","key":"730_CR22","first-page":"1374","volume":"11","author":"I Mandal","year":"2017","unstructured":"Mandal, I.: Machine learning algorithms for the creation of clinical healthcare enterprise systems. Enterp. Inf. Syst. 11(9), 1374\u20131400 (2017)","journal-title":"Enterp. Inf. Syst."},{"issue":"4","key":"730_CR23","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1007\/s00521-015-2103-9","volume":"28","author":"E Ali\u010dkovi\u0107","year":"2017","unstructured":"Ali\u010dkovi\u0107, E., Subasi, A.: Breast cancer diagnosis using GA feature selection and rotation forest. Neural Comput. Appl. 28(4), 753\u2013763 (2017)","journal-title":"Neural Comput. Appl."},{"key":"730_CR24","volume-title":"Uncertain rule-based fuzzy logic systems: introduction and new directions","author":"JM Mendel","year":"2001","unstructured":"Mendel, J.M.: Uncertain rule-based fuzzy logic systems: introduction and new directions. Prentice Hall PTR, Upper Saddle River (2001)"},{"issue":"7","key":"730_CR25","doi-asserted-by":"publisher","first-page":"2677","DOI":"10.1016\/j.eswa.2012.11.007","volume":"40","author":"R Stoean","year":"2013","unstructured":"Stoean, R., Stoean, C.: Modeling medical decision making by support vector machines, explaining by rules of evolutionary algorithms with feature selection. Expert Syst. Appl. 40(7), 2677\u20132686 (2013)","journal-title":"Expert Syst. Appl."},{"issue":"4","key":"730_CR26","doi-asserted-by":"publisher","first-page":"1476","DOI":"10.1016\/j.eswa.2013.08.044","volume":"41","author":"B Zheng","year":"2014","unstructured":"Zheng, B., Yoon, S.W., Lam, S.S.: Breast cancer diagnosis based on feature extraction using a hybrid of K-means and support vector machine algorithms. Expert Syst. Appl. 41(4), 1476\u20131482 (2014)","journal-title":"Expert Syst. Appl."},{"issue":"7","key":"730_CR27","doi-asserted-by":"publisher","first-page":"3410","DOI":"10.1016\/j.eswa.2014.12.025","volume":"42","author":"CK Lim","year":"2015","unstructured":"Lim, C.K., Chan, C.S.: A weighted inference engine based on interval-valued fuzzy relational theory. Expert Syst. Appl. 42(7), 3410\u20133419 (2015)","journal-title":"Expert Syst. Appl."},{"issue":"12","key":"730_CR28","first-page":"207","volume":"17","author":"RA Khan","year":"2017","unstructured":"Khan, R.A., Suleman, T., Farooq, M.S., Rafiq, M.H., Tariq, M.A.: Data mining algorithms for classification of diagnostic cancer using genetic optimization algorithms. IJCSNS 17(12), 207 (2017)","journal-title":"IJCSNS"},{"issue":"1","key":"730_CR29","first-page":"29","volume":"5","author":"M Buscema","year":"2013","unstructured":"Buscema, M., Breda, M., Lodwick, W.: Training with Input selection and testing (TWIST) algorithm: a significant advance in pattern recognition performance of machine learning. J. Intell. Learn. Syst. Appl. 5(1), 29 (2013)","journal-title":"J. Intell. Learn. Syst. Appl."},{"issue":"2","key":"730_CR30","doi-asserted-by":"publisher","first-page":"69","DOI":"10.14257\/ijbsbt.2014.6.2.07","volume":"6","author":"D Tomar","year":"2014","unstructured":"Tomar, D., Agarwal, S.: Feature selection based least square twin support vector machine for diagnosis of heart disease. Int. J. Bio-Sci. Bio-Technol. 6(2), 69\u201382 (2014)","journal-title":"Int. J. Bio-Sci. Bio-Technol."},{"key":"730_CR31","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1016\/j.engappai.2015.08.003","volume":"45","author":"S-H Lee","year":"2015","unstructured":"Lee, S.-H.: Feature selection based on the center of gravity of BSWFMs using NEWFM. Eng. Appl. Artif. Intell. 45, 482\u2013487 (2015)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"730_CR32","first-page":"1","volume":"2013","author":"E Y\u0131lmaz","year":"2013","unstructured":"Y\u0131lmaz, E., K\u0131l\u0131k\u00e7\u0131er, \u00c7.: Determination of fetal state from cardiotocogram using LS-SVM with particle swarm optimization and binary decision tree. Comput. Math. Methods Med. 2013, 1\u20138 (2013)","journal-title":"Comput. Math. Methods Med."},{"issue":"09","key":"730_CR33","doi-asserted-by":"publisher","first-page":"32","DOI":"10.4236\/jcc.2014.29005","volume":"2","author":"EM Karabulut","year":"2014","unstructured":"Karabulut, E.M., Ibrikci, T.: Analysis of cardiotocogram data for fetal distress determination by decision tree based adaptive boosting approach. J. Comput. Commun. 2(09), 32\u201337 (2014)","journal-title":"J. Comput. Commun."},{"key":"730_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2015\/283532","volume":"2015","author":"S Ravindran","year":"2015","unstructured":"Ravindran, S., Jambek, A.B., Muthusamy, H., Neoh, S.-C.: A novel clinical decision support system using improved adaptive genetic algorithm for the assessment of fetal well-being. Comput. Math. Methods Med. 2015, 1\u201311 (2015)","journal-title":"Comput. Math. Methods Med."}],"container-title":["International Journal of Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40815-019-00730-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s40815-019-00730-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40815-019-00730-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T23:31:56Z","timestamp":1599003116000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s40815-019-00730-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,3]]},"references-count":34,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2019,10]]}},"alternative-id":["730"],"URL":"https:\/\/doi.org\/10.1007\/s40815-019-00730-x","relation":{},"ISSN":["1562-2479","2199-3211"],"issn-type":[{"type":"print","value":"1562-2479"},{"type":"electronic","value":"2199-3211"}],"subject":[],"published":{"date-parts":[[2019,9,3]]},"assertion":[{"value":"11 August 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 November 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 September 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}