{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T18:06:07Z","timestamp":1792951567107,"version":"4.5.0"},"publisher-location":"New York, New York, USA","reference-count":28,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1145\/3041021.3054935","type":"proceedings-article","created":{"date-parts":[[2018,1,11]],"date-time":"2018-01-11T18:39:25Z","timestamp":1515695965000},"page":"1141-1147","source":"Crossref","is-referenced-by-count":3,"title":["Risk Quantification of Metabolic Syndrome with Quantum Particle Swarm Optimisation"],"prefix":"10.1145","author":[{"given":"Habeebah A.","family":"Kakudi","sequence":"first","affiliation":[{"name":"University of Malaya, Kuala Lumpur, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chu Kiong","family":"Loo","sequence":"additional","affiliation":[{"name":"University of Malaya, Kuala Lumpur, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kitsuchart","family":"Pasupa","sequence":"additional","affiliation":[{"name":"King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","reference":[{"key":"key-10.1145\/3041021.3054935-1","doi-asserted-by":"crossref","unstructured":"W. Ahrens, L. A. Moreno, S. Marild, D. Molnar, A. Siani, S. De Henauw, J. Bohmann, K. Gunther, C. Hadjigeorgiou, L. Iacoviello, L. Lissner, T. Veidebaum, H. Pohlabeln, and I. Pigeot. Metabolic syndrome in young children: definitions and results of the idefics study. Int J Obes (Lond), 38 Suppl 2:S4--14, Sep 2014.","DOI":"10.1038\/ijo.2014.130"},{"key":"key-10.1145\/3041021.3054935-2","doi-asserted-by":"crossref","unstructured":"M. S. Al-Zahrani, N. F. Bissada, and E. A. Borawski. Obesity and periodontal disease in young, middle-aged, and older adults. Journal of periodontology, 74(5):610--615, 2003.","DOI":"10.1902\/jop.2003.74.5.610"},{"key":"key-10.1145\/3041021.3054935-3","doi-asserted-by":"crossref","unstructured":"K. Alberti, R. H. Eckel, S. M. Grundy, P. Z. Zimmet, J. I. Cleeman, K. A.Donato, J.-C. Fruchart, W. P. T. James, C. M. Loria, and S. C. Smith. Harmonizing the metabolic syndrome a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; american heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity. Circulation, 120(16):1640--1645, 2009.","DOI":"10.1161\/CIRCULATIONAHA.109.192644"},{"key":"key-10.1145\/3041021.3054935-4","doi-asserted-by":"crossref","unstructured":"K. G. M. M. Alberti, P. Zimmet, and J. Shaw. Metabolic syndrome-new world-wide definition. a consensus statement from the international diabetes federation. Diabetic medicine, 23(5):469--480, 2006.","DOI":"10.1111\/j.1464-5491.2006.01858.x"},{"key":"key-10.1145\/3041021.3054935-5","doi-asserted-by":"crossref","unstructured":"K. G. M. M. Alberti and P. f. Zimmet.Definition, diagnosis and classification of diabetes mellitus and its complications. part 1: diagnosis and classification of diabetes mellitus. provisional report of a who consultation. Diabetic medicine, 15(7):539--553, 1998.","DOI":"10.1002\/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-S"},{"key":"key-10.1145\/3041021.3054935-6","unstructured":"B. Balkau, M. A. Charles, T. Drivsholm, K. Borch-Johnsen, N. Wareham, J. S.Yudkin, R. Morris, I. Zavaroni, R. van Dam, E. Feskins, R. Gabriel, M. Diet, P. Nilsson, and B. Hedblad. European group for the study of insulin resistance (egir). frequency of the who metabolic syndrome in european cohorts, and an alternative definition of an insulin resistance syndrome. Diabetes Metabolism, 20, 2002."},{"key":"key-10.1145\/3041021.3054935-7","doi-asserted-by":"crossref","unstructured":"A. Chu, R. Kalaba, and K. Spingarn. A comparison of two methods for determining the weights of belonging to fuzzy sets.Journal of Optimization theory and applications,27(4):531--538, 1979.","DOI":"10.1007\/BF00933438"},{"key":"key-10.1145\/3041021.3054935-8","unstructured":"R. Eberhart, P. Simpson, and R. Dobbins. Computational intelligence PC tools. Academic Press Professional, Inc., 1996."},{"key":"key-10.1145\/3041021.3054935-9","doi-asserted-by":"crossref","unstructured":"S. M. Grundy, H. B. Brewer, J. I. Cleeman, S. C. Smith, C. Lenfant, and f. t. C. Participants. Definition of metabolic syndrome: Report of the national heart, lung, and blood institute\/american heart association conference on scientific issues related to definition.Circulation, 109(3):433--438, 2004.","DOI":"10.1161\/01.CIR.0000111245.75752.C6"},{"key":"key-10.1145\/3041021.3054935-10","doi-asserted-by":"crossref","unstructured":"S. M. Grundy, J. I. Cleeman, S. R. Daniels, K. A. Donato, R. H. Eckel, B. A.Franklin, D. J. Gordon, R. M. Krauss, P. J. Savage, S. C. Smith, J. A.Spertus, and F. Costa.Diagnosis and management of the metabolic syndrome. An American Heart Association\/National Heart, Lung, and BloodInstitute Scientific Statement, 112(17):2735--2752, 2005.","DOI":"10.1161\/CIRCULATIONAHA.105.169404"},{"key":"key-10.1145\/3041021.3054935-11","doi-asserted-by":"crossref","unstructured":"T. Liu, L. Jiao, W. Ma, J. Ma, and R. Shang. A new quantum-behaved particle swarm optimization based on culturalevolution mechanism for multiobjective problems. Knowledge-Based Systems, 101:90--99, 2016.","DOI":"10.1016\/j.knosys.2016.03.009"},{"key":"key-10.1145\/3041021.3054935-12","doi-asserted-by":"crossref","unstructured":"J. Olza, M. Gil-Campos, R. Leis, G. Bueno, C. Aguilera, M. Valle, R. Canete, R. Tojo, L. Moreno, and A. Gil. Presence of the metabolic syndrome in obese children at prepubertal age. Annals of Nutrition and Metabolism, 58(4):343--350, 2011.","DOI":"10.1159\/000331996"},{"key":"key-10.1145\/3041021.3054935-13","unstructured":"W. H. Organisation. Global report on diabetes. Technical report, 2016."},{"key":"key-10.1145\/3041021.3054935-14","unstructured":"W. H. Organization. Definition, diagnosis and classification of diabetes mellitus and itscomplications: report of a who consultation. part 1, diagnosis and classification of diabetes mellitus. WHO, Geneva, 1999."},{"key":"key-10.1145\/3041021.3054935-15","doi-asserted-by":"crossref","unstructured":"P. I. Parikka, M. Laakso, J. G. Eriksson, J. G. Lakka, J. Lindstrom,M. Pletonen, S. Aunola, S. A. Kiukaanneimi, M. Uusitupa, and J. Tuomilehto. Leisure-time physical activity and the metabolic syndrome in the finnish diabetes prevention study. Diabetes Care, 33, 2010.","DOI":"10.2337\/dc09-2155"},{"key":"key-10.1145\/3041021.3054935-16","doi-asserted-by":"crossref","unstructured":"M. S. Pepe. The statistical evaluation of medical tests for classification and prediction. Oxford University Press, USA, 2003.","DOI":"10.1093\/oso\/9780198509844.001.0001"},{"key":"key-10.1145\/3041021.3054935-17","doi-asserted-by":"crossref","unstructured":"G. M. Reaven.Role of insulin resistance in human disease. Diabetes, 37, 1988.","DOI":"10.2337\/diab.37.12.1595"},{"key":"key-10.1145\/3041021.3054935-18","doi-asserted-by":"crossref","unstructured":"T. L. Saaty. Analytic hierarchy process. In Encyclopedia of operations research and management science,pages 52--64. Springer, 2013.","DOI":"10.1007\/978-1-4419-1153-7_31"},{"key":"key-10.1145\/3041021.3054935-19","doi-asserted-by":"crossref","unstructured":"T. L. Saaty and L. G. Vargas.Comparison of eigenvalue, logarithmic least squares and least squares methods in estimating ratios.Mathematical modelling, 5(5):309--324, 1984.","DOI":"10.1016\/0270-0255(84)90008-3"},{"key":"key-10.1145\/3041021.3054935-20","doi-asserted-by":"crossref","unstructured":"J. Sangjin, J. Yu Mi, S. Sang-Oh, C. Yeon-Jung, and Y. Chan-Hyun. A novel model for metabolic syndrome risk quantification based on areal similarity degree. IEEE Transactions on Biomedical Engineering, 61(3):665--679,2014.","DOI":"10.1109\/TBME.2013.2286197"},{"key":"key-10.1145\/3041021.3054935-21","doi-asserted-by":"crossref","unstructured":"T. Shah, S. S. Jonnalagadda, J. R. Kicklighter, S. Diwan, and B. L. Hopkins. Prevalence of metabolic syndrome risk factors among young adult asian indians. Journal of immigrant health, 7(2):117--125, 2005.","DOI":"10.1007\/s10903-005-2645-5"},{"key":"key-10.1145\/3041021.3054935-22","doi-asserted-by":"crossref","unstructured":"R. Simmons, K. Alberti, E. Gale, S. Colagiuri, J. Tuomilehto, Q. Qiao, A. Ramachandran, N. Tajima, I. B. Mirchov, and A. Ben-Nakhi. The metabolic syndrome: useful concept or clinical tool? report of a who expert consultation. Diabetologia, 53(4):600--605, 2010.","DOI":"10.1007\/s00125-009-1620-4"},{"key":"key-10.1145\/3041021.3054935-23","doi-asserted-by":"crossref","unstructured":"I. Soldatovic, R. Vukovic, D. Culafic, M. Gajic, and V. Dimitrijevic-Sreckovic. sims score: Simple method for quantifying metabolic syndrome. Plos One, 11(1):10, 2016.","DOI":"10.1371\/journal.pone.0146143"},{"key":"key-10.1145\/3041021.3054935-24","doi-asserted-by":"crossref","unstructured":"B. Srdjevic and Z. Srdjevic. Bi-criteria evolution strategy in estimating weights from the ahp ratio-scale matrices. Applied Mathematics and Computation, 218(4):1254--1266, 2011.","DOI":"10.1016\/j.amc.2011.06.006"},{"key":"key-10.1145\/3041021.3054935-25","doi-asserted-by":"crossref","unstructured":"J. Sun, B. Feng, and W. Xu. Particle swarm optimization with particles having quantum behavior. In Evolutionary Computation, 2004. CEC2004. Congress on, volume 1, pages 325--331. IEEE, 2004.","DOI":"10.1109\/CEC.2004.1330875"},{"key":"key-10.1145\/3041021.3054935-26","doi-asserted-by":"crossref","unstructured":"N. G. Thaker, T. N. Ali, M. E. Porter, T. W. Feeley, R. S. Kaplan, and S. J.Frank. Communicating value in health care using radar charts: A case study of prostate cancer. Journal of Oncology Practice, 12(9):813--820, 2016.","DOI":"10.1200\/JOP.2016.011320"},{"key":"key-10.1145\/3041021.3054935-27","unstructured":"S. Yang and M. Wang.A quantum particle swarm optimization. In Evolutionary Computation, 2004. CEC2004. Congress on, volume 1, pages 320--324. IEEE, 2004."},{"key":"key-10.1145\/3041021.3054935-28","doi-asserted-by":"crossref","unstructured":"H. Zhang, Y. Hou, J. Zhang, X. Qi, and F. Wang. A new method for nondestructive quality evaluation of the resistance spot welding based on the radar chart method and the decision tree classifier. The International Journal of Advanced Manufacturing Technology, 78(5--8):841--851, 2015.","DOI":"10.1007\/s00170-014-6654-1"}],"event":{"name":"the 26th International Conference","location":"Perth, Australia","acronym":"WWW '17 Companion","number":"26","sponsor":["SIGWEB, ACM Special Interest Group on Hypertext, Hypermedia, and Web","IW3C2, International World Wide Web Conference Committee"],"start":{"date-parts":[[2017,4,3]]},"end":{"date-parts":[[2017,4,7]]}},"container-title":["Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3041021.3054935","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=3054935&ftid=1865301&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T03:03:30Z","timestamp":1750215810000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=3041021.3054935"}},"subtitle":[],"proceedings-subject":"World Wide Web Companion","short-title":[],"issued":{"date-parts":[[2017]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1145\/3041021.3054935","relation":{},"subject":[],"published":{"date-parts":[[2017]]}}}