{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T07:07:10Z","timestamp":1760080030550},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2017,1,27]],"date-time":"2017-01-27T00:00:00Z","timestamp":1485475200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Romanian Ministry of National Education (MEN) - Research and the Executive Agency for Higher Education Research Development and Innovation Funding (UEFISCDI)","award":["Grant no. 26\/2014, code PN-II-PT-PCCA-2013-4-1153"],"award-info":[{"award-number":["Grant no. 26\/2014, code PN-II-PT-PCCA-2013-4-1153"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1007\/s11063-017-9585-7","type":"journal-article","created":{"date-parts":[[2017,1,27]],"date-time":"2017-01-27T11:00:20Z","timestamp":1485514820000},"page":"811-827","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Interpreting Decision Support from Multiple Classifiers for Predicting Length of Stay in Patients with Colorectal Carcinoma"],"prefix":"10.1007","volume":"46","author":[{"given":"Ruxandra","family":"Stoean","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Catalin","family":"Stoean","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adrian","family":"Sandita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniela","family":"Ciobanu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cristian","family":"Mesina","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,1,27]]},"reference":[{"key":"9585_CR1","doi-asserted-by":"publisher","unstructured":"Arizmendi C, Sierra DA, Vellido A, Romero E (2014) Automated classification of brain tumours from short echo time in vivo MRS data using Gaussian decomposition and Bayesian neural networks. Expert Syst Appl 41(11):5296\u20135307. doi: 10.1016\/j.eswa.2014.02.031 . http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417414001079","DOI":"10.1016\/j.eswa.2014.02.031"},{"key":"9585_CR2","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.jbi.2014.11.010","volume":"53","author":"S Belciug","year":"2015","unstructured":"Belciug S, Gorunescu F (2015) Improving hospital bed occupancy and resource utilization through queuing modeling and evolutionary computation. J Biomed Inform 53:261\u2013269","journal-title":"J Biomed Inform"},{"key":"9585_CR3","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.cie.2014.04.016","volume":"78","author":"P Bhattacharjee","year":"2014","unstructured":"Bhattacharjee P, Ray PK (2014) Patient flow modelling and performance analysis of healthcare delivery processes in hospitals: a review and reflections. Comput Ind Eng 78:299\u2013312","journal-title":"Comput Ind Eng"},{"issue":"2","key":"9585_CR4","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1023\/A:1018054314350","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman L (1996) Bagging predictors. Mach Learn 24(2):123\u2013140. doi: 10.1023\/A:1018054314350","journal-title":"Mach Learn"},{"issue":"1","key":"9585_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45(1):5\u201332. doi: 10.1023\/A:1010933404324","journal-title":"Mach Learn"},{"key":"9585_CR6","doi-asserted-by":"crossref","unstructured":"Czibula G, Cri\u015fan GC, Pintea CM, Czibula IG (2013) Soft computing approaches on the bandwidth problem. Informatica 24(2):169\u2013180. http:\/\/dl.acm.org\/citation.cfm?id=2773202.2773203","DOI":"10.15388\/Informatica.2013.390"},{"issue":"2\u20133","key":"9585_CR7","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1007\/BF00993042","volume":"13","author":"KA Jong De","year":"1993","unstructured":"De Jong KA, Spears WM, Gordon DF (1993) Using genetic algorithms for concept learning. Mach Learn 13(2\u20133):161\u2013188. doi: 10.1007\/BF00993042","journal-title":"Mach Learn"},{"key":"9585_CR8","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-662-05094-1","volume-title":"Introduction to evolutionary computing","author":"AE Eiben","year":"2003","unstructured":"Eiben AE, Smith JE (2003) Introduction to evolutionary computing. Springer, Berlin"},{"issue":"7","key":"9585_CR9","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1111\/j.1463-1318.2010.02277.x","volume":"13","author":"O Faiz","year":"2011","unstructured":"Faiz O, Haji A, Burns E, Bottle A, Kennedy R, Aylin P (2011) Hospital stay amongst patients undergoing major elective colorectal surgery: predicting prolonged stay and readmissions in nhs hospitals. Colorectal Dis 13(7):816\u2013822","journal-title":"Colorectal Dis"},{"key":"9585_CR10","unstructured":"Fern\u00e1ndez-Delgado M, Cernadas E, Barro S, Amorim D (2014) Do we need hundreds of classifiers to solve real world classification problems? J Mach Learn Res 15(1):3133\u20133181. http:\/\/dl.acm.org\/citation.cfm?id=2627435.2697065"},{"key":"9585_CR11","unstructured":"Freund Y, Schapire RE (1996) Experiments with a new boosting algorithm. In: Saitta L (ed) Proceedings of the thirteenth international conference on machine learning (ICML 1996). Morgan Kaufmann, pp\u00a0148\u2013156"},{"key":"9585_CR12","doi-asserted-by":"publisher","unstructured":"Garca-Garaluz E, Atencia M, Joya G, Garca-Lagos F, Sandoval F (2011) Hopfield networks for identification of delay differential equations with an application to dengue fever epidemics in Cuba. Neurocomputing 74(16):2691\u20132697. doi: 10.1016\/j.neucom.2011.03.022 . http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0925231211002402 . Advances in extreme learning machine: theory and applications biological inspired systems. computational and ambient intelligence selected papers of the 10th international work-conference on artificial neural networks (IWANN2009)","DOI":"10.1016\/j.neucom.2011.03.022"},{"key":"9585_CR13","volume-title":"Data mining\u2014concepts, models and techniques, intelligent systems reference library","author":"F Gorunescu","year":"2011","unstructured":"Gorunescu F (2011) Data mining\u2014concepts, models and techniques, intelligent systems reference library, vol 12. Springer, Berlin"},{"key":"9585_CR14","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.jbi.2014.02.001","volume":"49","author":"F Gorunescu","year":"2014","unstructured":"Gorunescu F, Belciug S (2014) Evolutionary strategy to develop learning-based decision systems. Application to breast cancer and liver fibrosis stadialization. J Biomed Inform 49:112\u2013118","journal-title":"J Biomed Inform"},{"key":"9585_CR15","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-21606-5","volume-title":"The elements of statistical learning. Springer series in statistics","author":"T Hastie","year":"2001","unstructured":"Hastie T, Tibshirani R, Friedman J (2001) The elements of statistical learning. Springer series in statistics. Springer, New York"},{"key":"9585_CR16","volume-title":"Neural networks: a comprehensive foundation","author":"S Haykin","year":"1998","unstructured":"Haykin S (1998) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall PTR, Englewood Cliffs","edition":"2"},{"issue":"2","key":"9585_CR17","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1109\/TSMCC.2008.2007252","volume":"39","author":"ER Hruschka","year":"2009","unstructured":"Hruschka ER, Campello RJGB, Freitas AA, De Carvalho ACPLF (2009) A survey of evolutionary algorithms for clustering. Trans Syst Man Cybern Part C 39(2):133\u2013155. doi: 10.1109\/TSMCC.2008.2007252","journal-title":"Trans Syst Man Cybern Part C"},{"issue":"2","key":"9585_CR18","first-page":"415","volume":"13","author":"CW Hsu","year":"2004","unstructured":"Hsu CW, Lin CJ (2004) A comparison of methods for multi-class support vector machines. IEEE Trans Neural Netw 13(2):415\u2013425","journal-title":"IEEE Trans Neural Netw"},{"issue":"1","key":"9585_CR19","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1186\/1472-6963-12-77","volume":"12","author":"M Kelly","year":"2012","unstructured":"Kelly M, Sharp L, Dwane F, Kelleher T, Comber H (2012) Factors predicting hospital length-of-stay and readmission after colorectal resection: a population-based study of elective and emergency admissions. BMC Health Serv Res 12(1):77","journal-title":"BMC Health Serv Res"},{"key":"9585_CR20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19644-7_29","volume-title":"Short-term wind energy forecasting using support vector regression","author":"O Kramer","year":"2011","unstructured":"Kramer O, Gieseke F (2011) Short-term wind energy forecasting using support vector regression. Springer, Berlin. doi: 10.1007\/978-3-642-19644-7_29"},{"issue":"10","key":"9585_CR21","doi-asserted-by":"crossref","first-page":"2183","DOI":"10.1007\/s00268-009-0148-6","volume":"33","author":"A Leung","year":"2009","unstructured":"Leung A, Gibbons R, Vu H (2009) Predictors of length of stay following colorectal resection for neoplasms in 183 veterans affairs patients. World J Surg 33(10):2183\u20132188","journal-title":"World J Surg"},{"key":"9585_CR22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-16531-8_2","volume-title":"On meta-heuristics in optimization and data analysis. Application to geosciences","author":"H Luchian","year":"2015","unstructured":"Luchian H, Breaban ME, Bautu A (2015) On meta-heuristics in optimization and data analysis. Application to geosciences. Springer, Cham. doi: 10.1007\/978-3-319-16531-8_2"},{"issue":"3","key":"9585_CR23","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1016\/j.ejor.2006.04.051","volume":"183","author":"D Martens","year":"2007","unstructured":"Martens D, Baesens B, Gestel TV, Vanthienen J (2007) Comprehensible credit scoring models using rule extraction from support vector machines. Eur J Oper Res 183(3):1466\u20131476","journal-title":"Eur J Oper Res"},{"issue":"2","key":"9585_CR24","doi-asserted-by":"crossref","first-page":"532","DOI":"10.3748\/wjg.v20.i2.532","volume":"20","author":"DS Perng","year":"2014","unstructured":"Perng DS, Lu IC, Shi HY, Lin CW, Liu KW, Su YF, Lee KT (2014) Incidence trends and predictors for cost and average lengths of stay in colorectal cancer surgery. World J Gastroenterol 20(2):532\u2013538","journal-title":"World J Gastroenterol"},{"key":"9585_CR25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07407-8","volume-title":"Multimodal optimization by means of evolutionary algorithms. Natural computing series","author":"M Preuss","year":"2015","unstructured":"Preuss M (2015) Multimodal optimization by means of evolutionary algorithms. Natural computing series. Springer, Berlin. doi: 10.1007\/978-3-319-07407-8"},{"key":"9585_CR26","volume-title":"C4.5: programs for machine learning","author":"R Quinlan","year":"1993","unstructured":"Quinlan R (1993) C4.5: programs for machine learning. Morgan Kaufmann, Los Altos"},{"key":"9585_CR27","doi-asserted-by":"publisher","unstructured":"Riera-Ledesma J, Salazar-Gonzlez JJ (2005) A heuristic approach for the travelling purchaser problem. Eur J Oper Res 162(1):142\u2013152. doi: 10.1016\/j.ejor.2003.10.032 . http:\/\/www.sciencedirect.com\/science\/article\/pii\/S037722170300821X . Logistics: from theory to application","DOI":"10.1016\/j.ejor.2003.10.032"},{"key":"9585_CR28","doi-asserted-by":"publisher","unstructured":"Hoffmann F (2004) Combining boosting and evolutionary algorithms for learning of fuzzy classification rules. Fuzzy Sets Syst 141(1):47\u201358. doi: 10.1016\/S0165-0114(03)00113-1","DOI":"10.1016\/S0165-0114(03)00113-1"},{"key":"9585_CR29","doi-asserted-by":"crossref","unstructured":"Stoean C, Stoean R (2009) Evolution of cooperating classification rules with an archiving strategy to underpin collaboration. In: Teodorescu H-N, Watada J, Jain LC (eds) Intelligent systems and technologies: methods and applications. Springer, Berlin, pp\u00a047\u201365","DOI":"10.1007\/978-3-642-01885-5_3"},{"key":"9585_CR30","doi-asserted-by":"publisher","unstructured":"Stoean C, Stoean R (2014) Post-evolution of variable-length class prototypes to unlock decision making within support vector machines. Appl Soft Comput 25:159\u2013173. doi: 10.1016\/j.asoc.2014.09.017 . http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1568494614004694","DOI":"10.1016\/j.asoc.2014.09.017"},{"key":"9585_CR31","first-page":"1436","volume":"1","author":"R Stoean","year":"2007","unstructured":"Stoean R, Preuss M, Stoean C, Dumitrescu D (2007) Concerning the potential of evolutionary support vector machines. Proc IEEE Congr Evol Comput 1:1436\u20131443","journal-title":"Proc IEEE Congr Evol Comput"},{"key":"9585_CR32","unstructured":"Stoean R, Stoean C, Preuss M, Dumitrescu D (2006) Evolutionary multi-class support vector machines for classification. In: Proceedings of international conference on computers and communications\u2014ICCC 2006, Baile Felix Spa - Oradea, Romania, pp 423\u2013428"},{"key":"9585_CR33","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1007\/978-3-319-19258-1_37","volume-title":"Advances in computational intelligence lecture notes in computer science","author":"R Stoean","year":"2015","unstructured":"Stoean R, Stoean C, Sandita A, Ciobanu D, Mesina C (2015) Ensemble of classifiers for length of stay prediction in colorectal cancer. In: Rojas I, Joya G, Catala A (eds) Advances in computational intelligence lecture notes in computer science, vol 9094. Springer, Berlin, pp 444\u2013457"},{"key":"9585_CR34","volume-title":"Statistical learning theory","author":"V Vapnik","year":"1998","unstructured":"Vapnik V (1998) Statistical learning theory. Wiley, New York"},{"key":"9585_CR35","doi-asserted-by":"publisher","unstructured":"Zaefferer M, Stork J, Friese M, Fischbach A, Naujoks B, Bartz-Beielstein T (2014) Efficient global optimization for combinatorial problems. In: Proceedings of the 2014 annual conference on genetic and evolutionary computation, GECCO \u201914. ACM, New York, pp 871\u2013878. doi: 10.1145\/2576768.2598282","DOI":"10.1145\/2576768.2598282"},{"key":"9585_CR36","doi-asserted-by":"publisher","unstructured":"Zaharie D, Lungeanu D, Zamfirache F (2008) Interactive search of rules in medical data using multiobjective evolutionary algorithms. In: Proceedings of the 10th annual conference companion on genetic and evolutionary computation, GECCO \u201908. ACM, New York, pp 2065\u20132072. doi: 10.1145\/1388969.1389023","DOI":"10.1145\/1388969.1389023"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-017-9585-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9585-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9585-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,30]],"date-time":"2020-09-30T21:26:59Z","timestamp":1601501219000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-017-9585-7"}},"subtitle":["What can a Professional Get from the Opinions of Different Models?"],"short-title":[],"issued":{"date-parts":[[2017,1,27]]},"references-count":36,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2017,12]]}},"alternative-id":["9585"],"URL":"https:\/\/doi.org\/10.1007\/s11063-017-9585-7","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"value":"1370-4621","type":"print"},{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,1,27]]}}}