{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T09:27:24Z","timestamp":1766136444155},"reference-count":58,"publisher":"Elsevier BV","issue":"1","content-domain":{"domain":["aiimjournal.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Artificial Intelligence in Medicine"],"published-print":{"date-parts":[[2014,1]]},"DOI":"10.1016\/j.artmed.2013.10.001","type":"journal-article","created":{"date-parts":[[2013,10,18]],"date-time":"2013-10-18T04:00:39Z","timestamp":1382068839000},"page":"53-64","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":25,"title":["White box radial basis function classifiers with component selection for clinical prediction models"],"prefix":"10.1016","volume":"60","author":[{"given":"Vanya","family":"Van Belle","sequence":"first","affiliation":[]},{"given":"Paulo","family":"Lisboa","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.artmed.2013.10.001_bib0005","series-title":"Statistical learning theory","author":"Vapnik","year":"1998"},{"issue":"3","key":"10.1016\/j.artmed.2013.10.001_bib0010","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1023\/A:1018628609742","article-title":"Least squares support vector machine classifiers","volume":"9","author":"Suykens","year":"1999","journal-title":"Neural Processing Letters"},{"key":"10.1016\/j.artmed.2013.10.001_bib0015","series-title":"Least squares support vector machines","author":"Suykens","year":"2002"},{"issue":"5439","key":"10.1016\/j.artmed.2013.10.001_bib0020","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1126\/science.286.5439.531","article-title":"Molecular classification of cancer: class discovery and class prediction by gene expression monitoring","volume":"286","author":"Golub","year":"1999","journal-title":"Science"},{"issue":"10","key":"10.1016\/j.artmed.2013.10.001_bib0025","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1093\/bioinformatics\/16.10.906","article-title":"Support vector machine classification and validation of cancer tissue samples using microarray expression data","volume":"16","author":"Furey","year":"2000","journal-title":"Bioinformatics"},{"key":"10.1016\/j.artmed.2013.10.001_bib0030","series-title":"Proceedings of the ninth international workshop on machine learning (ML92)","first-page":"249","article-title":"A practical approach to feature selection","author":"Kira","year":"1992"},{"issue":"6","key":"10.1016\/j.artmed.2013.10.001_bib0035","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1109\/TPAMI.2007.1093","article-title":"Iterative RELIEF for feature weighting: algorithms, theories, and applications","volume":"29","author":"Sun","year":"2007","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.artmed.2013.10.001_bib0040","series-title":"Proceedings of the ninth national conference on artificial intelligence","first-page":"547","article-title":"Learning with many irrelevant features","author":"Almuallim","year":"1991"},{"issue":"1","key":"10.1016\/j.artmed.2013.10.001_bib0045","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","article-title":"Wrappers for feature subset selection","volume":"97","author":"Kohavi","year":"1997","journal-title":"Artificial Intelligence"},{"key":"10.1016\/j.artmed.2013.10.001_bib0050","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"Guyon","year":"2003","journal-title":"Journal of Machine Learning Research"},{"issue":"1\u20133","key":"10.1016\/j.artmed.2013.10.001_bib0055","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1023\/A:1012487302797","article-title":"Gene selection for cancer classification using support vector machines","volume":"46","author":"Guyon","year":"2002","journal-title":"Machine Learning"},{"key":"10.1016\/j.artmed.2013.10.001_bib0060","series-title":"Advances in neural information processing systems 13","first-page":"668","article-title":"Feature selection for SVMs","author":"Weston","year":"2000"},{"key":"10.1016\/j.artmed.2013.10.001_bib0065","first-page":"1357","article-title":"Variable selection using svm based criteria","volume":"3","author":"Rakotomamonjy","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.artmed.2013.10.001_bib0070","series-title":"A feature selection Newton method for support vector machine classification. Tech. Rep. 02-03","author":"Fung","year":"2002"},{"key":"10.1016\/j.artmed.2013.10.001_bib0075","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/S0004-3702(97)00063-5","article-title":"Selection of relevant features and examples in machine learning","volume":"97","author":"Blum","year":"1997","journal-title":"Artificial Intelligence"},{"key":"10.1016\/j.artmed.2013.10.001_bib0080","first-page":"1439","article-title":"Use of the zero norm with linear models and kernel methods","volume":"3","author":"Weston","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.artmed.2013.10.001_bib0085","series-title":"Proceedings of the fifteenth international conference on machine learning (ICML)","first-page":"82","article-title":"Feature selection via concave minimization and support vector machines","author":"Bradley","year":"1998"},{"issue":"1\u20133","key":"10.1016\/j.artmed.2013.10.001_bib0090","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s10994-005-1505-9","article-title":"Combined svm-based feature selection and classification","volume":"61","author":"Neumann","year":"2005","journal-title":"Machine Learning"},{"key":"10.1016\/j.artmed.2013.10.001_bib0095","series-title":"Proceedings of the Seventh IEEE International Conference on Data Mining Workshops. ICDMW","first-page":"231","article-title":"Feature selection for nonlinear kernel support vector machines","author":"Mangasarian","year":"2007"},{"key":"10.1016\/j.artmed.2013.10.001_bib0100","series-title":"Proceedings of the 27th international conference on machine learning (ICML)","first-page":"1047","article-title":"Learning sparse svm for feature selection on very high dimensional datasets","author":"Tan","year":"2010"},{"issue":"1","key":"10.1016\/j.artmed.2013.10.001_bib0105","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.ins.2010.08.047","article-title":"Simultaneous feature selection and classification using kernel-penalized support vector machines","volume":"181","author":"Maldonado","year":"2011","journal-title":"Information Sciences"},{"issue":"2","key":"10.1016\/j.artmed.2013.10.001_bib0110","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1109\/TNN.2005.863472","article-title":"Orthogonal search-based rule extraction (OSRE) for trained neural networks: a practical and efficient approach","volume":"17","author":"Etchells","year":"2006","journal-title":"IEEE Transactions on Neural Networks"},{"key":"10.1016\/j.artmed.2013.10.001_bib0115","series-title":"Rule extraction from support vector machines; vol. 80 of studies in computational intelligence","first-page":"33","article-title":"Rule extraction from support vector machines: an overview of issues and application in credit scoring","author":"Martens","year":"2008"},{"key":"10.1016\/j.artmed.2013.10.001_bib0120","series-title":"Generalized additive models","author":"Hastie","year":"1990"},{"key":"10.1016\/j.artmed.2013.10.001_bib0125","series-title":"Componentwise least squares support vector machines chap. Support vector machines: theory and applications","first-page":"77","author":"Pelckmans","year":"2005"},{"key":"10.1016\/j.artmed.2013.10.001_bib0130","series-title":"Support vector regression with ANOVA decomposition kernels; chap. Advances in kernel methods: support vector learning","first-page":"285","author":"Stitson","year":"1999"},{"key":"10.1016\/j.artmed.2013.10.001_bib0135","series-title":"Clinical prediction models: a practical approach to development, validation and updating, statistics for biology and health","author":"Steyerberg","year":"2009"},{"key":"10.1016\/j.artmed.2013.10.001_bib0140","article-title":"Regression modeling strategies. With applications to linear models logistic regression and survival analysis","author":"Harrell","year":"2001"},{"issue":"4","key":"10.1016\/j.artmed.2013.10.001_bib0145","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1080\/00401706.1995.10484371","article-title":"Better subset regression using the nonnegative garrote","volume":"37","author":"Breiman","year":"1995","journal-title":"Technometrics"},{"issue":"5","key":"10.1016\/j.artmed.2013.10.001_bib0150","doi-asserted-by":"crossref","first-page":"2272","DOI":"10.1214\/009053606000000722","article-title":"Component selection and smoothing in multivariate nonparametric regression","volume":"34","author":"Lin","year":"2006","journal-title":"Annals of Statistics"},{"issue":"5","key":"10.1016\/j.artmed.2013.10.001_bib0155","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1111\/j.1467-9868.2009.00718.x","article-title":"Sparse additive models","volume":"71","author":"Ravikumar","year":"2009","journal-title":"Journal of the Royal Statistical Society, Series B: Statistical Methodology"},{"key":"10.1016\/j.artmed.2013.10.001_bib0160","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1023\/A:1013903804720","article-title":"Structural modelling with sparse kernels","volume":"48","author":"Gunn","year":"2002","journal-title":"Machine Learning"},{"key":"10.1016\/j.artmed.2013.10.001_bib0165","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1098\/rsta.1909.0016","article-title":"Functions of positive and negative type and their connection with the theory of integral equations","volume":"209","author":"Mercer","year":"1909","journal-title":"Philosophical Transactions of the Royal Society A"},{"key":"10.1016\/j.artmed.2013.10.001_bib0170","series-title":"Proceedings of the 31st annual international conference of the IEEE engineering in medicine and biology society (EMBS)","first-page":"5913","article-title":"Development of a kernel function for clinical data","author":"Daemen","year":"2009"},{"issue":"5\u20136","key":"10.1016\/j.artmed.2013.10.001_bib0175","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1007\/s00041-008-9045-x","article-title":"Enhancing sparsity by reweighted l1 minimization","volume":"14","author":"Cand\u00e8s","year":"2008","journal-title":"Journal of Fourier Analysis and Applications"},{"issue":"4","key":"10.1016\/j.artmed.2013.10.001_bib0180","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1002\/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3","article-title":"The lasso method for variable selection in the Cox model","volume":"16","author":"Tibshirani","year":"1997","journal-title":"Statistics in Medicine"},{"key":"10.1016\/j.artmed.2013.10.001_bib0185","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1111\/j.1467-9868.2007.00581.x","article-title":"On the non-negative garrote estimator","volume":"69","author":"Yuan","year":"2007","journal-title":"Journal of the Royal Statistical Society, Series B: Statistical Methodology"},{"issue":"2","key":"10.1016\/j.artmed.2013.10.001_bib0190","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1109\/TSMCB.2009.2020435","article-title":"Coupled simulated annealing","volume":"40","author":"Xavier de Souza","year":"2010","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Part B"},{"issue":"3","key":"10.1016\/j.artmed.2013.10.001_bib0195","doi-asserted-by":"crossref","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach","volume":"44","author":"DeLong","year":"1988","journal-title":"Biometrics"},{"key":"10.1016\/j.artmed.2013.10.001_bib0200","series-title":"Advances in large margin classifiers","first-page":"61","article-title":"Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods","author":"Platt","year":"1999"},{"key":"10.1016\/j.artmed.2013.10.001_bib0205","series-title":"UCI machine learning repository","author":"Frank","year":"2010"},{"issue":"6","key":"10.1016\/j.artmed.2013.10.001_bib0210","doi-asserted-by":"crossref","first-page":"1014","DOI":"10.3923\/jas.2009.1014.1024","article-title":"Feature ranking by weighting and ISE criterion of nonparametric density estimation","volume":"9","author":"Wang","year":"2009","journal-title":"Journal of Applied Sciences"},{"key":"10.1016\/j.artmed.2013.10.001_bib0215","series-title":"Proceedings of the ninth IEEE international conference on tools with artificial intelligence","first-page":"532","article-title":"Dimensionality reduction for unsupervised data","author":"Dash","year":"1997"},{"key":"10.1016\/j.artmed.2013.10.001_bib0220","series-title":"Proceedings of the European conference on machine learning (ECML-94)","first-page":"171","article-title":"Estimating attributes: analysis and extensions of RELIEF","author":"Kononenko","year":"1994"},{"issue":"10","key":"10.1016\/j.artmed.2013.10.001_bib0225","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1109\/TPAMI.2003.1233899","article-title":"Probability density estimation from optimally condensed data samples","volume":"25","author":"Girolami","year":"2003","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"4","key":"10.1016\/j.artmed.2013.10.001_bib0230","first-page":"187","article-title":"Decision tree-based feature ranking using Manhattan hierarchical cluster criterion","volume":"6","author":"Yacob","year":"2012","journal-title":"International Journal of Engineering and Physical Sciences"},{"issue":"8","key":"10.1016\/j.artmed.2013.10.001_bib0235","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/34.85676","article-title":"A statistical-heuristic feature selection criterion for decision tree induction","volume":"13","author":"Zhou","year":"1991","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.artmed.2013.10.001_bib0240","series-title":"Proceedings of the 9th international conference on neural information processing 2002 (ICONIP\u201902), vol. 5","first-page":"2217","article-title":"Decision tree decomposition-based complex feature selection for text chunking","author":"Hwang","year":"2002"},{"issue":"8","key":"10.1016\/j.artmed.2013.10.001_bib0245","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1049\/iet-gtd.2008.0374","article-title":"Application of core vector machines for on-line voltage security assessment using a decision-tree-based feature selection algorithm","volume":"3","author":"Mohammadi","year":"2009","journal-title":"IET Generation Transmission Distribution"},{"key":"10.1016\/j.artmed.2013.10.001_bib0250","series-title":"C4.5: programs for machine learning","author":"Quinlan","year":"1993"},{"issue":"2","key":"10.1016\/j.artmed.2013.10.001_bib0255","first-page":"271","article-title":"Comparative study of attribute selection using gain ratio and correlation based feature selection","volume":"2","author":"Karegowda","year":"2010","journal-title":"International Journal of Information Technology and Knowledge Management"},{"key":"10.1016\/j.artmed.2013.10.001_bib0260","series-title":"Genetic algorithms in search, optimization and machine learning","author":"Goldberg","year":"1989"},{"issue":"SP 1","key":"10.1016\/j.artmed.2013.10.001_bib0265","first-page":"501","article-title":"Feature selection using FCBF in type II diabetes databases","volume":"17","author":"Balakrishnan","year":"2009","journal-title":"International Journal of the Computer, the Internet and the Management"},{"issue":"3","key":"10.1016\/j.artmed.2013.10.001_bib0270","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/S0933-3657(99)00041-X","article-title":"Generating concise and accurate classification rules for breast cancer diagnosis","volume":"18","author":"Setiono","year":"2000","journal-title":"Artificial Intelligence in Medicine"},{"key":"10.1016\/j.artmed.2013.10.001_bib0275","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1109\/69.774103","article-title":"Symbolic interpretation of artificial neural networks","volume":"11","author":"Taha","year":"1999","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"10","key":"10.1016\/j.artmed.2013.10.001_bib0280","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1016\/j.neunet.2005.01.008","article-title":"A novel information geometric approach to variable selection in mlp networks","volume":"18","author":"Eleuteri","year":"2005","journal-title":"Neural Networks"},{"issue":"1","key":"10.1016\/j.artmed.2013.10.001_bib0285","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0925-2312(97)00038-6","article-title":"Neurolinear: from neural networks to oblique decision rules","volume":"17","author":"Setiono","year":"1997","journal-title":"Neurocomputing"},{"issue":"1\u20134","key":"10.1016\/j.artmed.2013.10.001_bib0290","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/S0925-2312(00)00294-0","article-title":"Input selection based on an ensemble","volume":"34","author":"van de Laar","year":"2000","journal-title":"Neurocomputing"}],"container-title":["Artificial Intelligence in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0933365713001425?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0933365713001425?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2018,10,12]],"date-time":"2018-10-12T03:25:05Z","timestamp":1539314705000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0933365713001425"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,1]]},"references-count":58,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,1]]}},"alternative-id":["S0933365713001425"],"URL":"https:\/\/doi.org\/10.1016\/j.artmed.2013.10.001","relation":{},"ISSN":["0933-3657"],"issn-type":[{"value":"0933-3657","type":"print"}],"subject":[],"published":{"date-parts":[[2014,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"White box radial basis function classifiers with component selection for clinical prediction models","name":"articletitle","label":"Article Title"},{"value":"Artificial Intelligence in Medicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.artmed.2013.10.001","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"Copyright \u00a9 2013 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}