{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T02:32:22Z","timestamp":1772159542917,"version":"3.50.1"},"reference-count":38,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2021,8,1]],"date-time":"2021-08-01T00:00:00Z","timestamp":1627776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2021,8,1]],"date-time":"2021-08-01T00:00:00Z","timestamp":1627776000000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2021,8]]},"DOI":"10.1109\/jbhi.2021.3054592","type":"journal-article","created":{"date-parts":[[2021,1,29]],"date-time":"2021-01-29T15:32:46Z","timestamp":1611934366000},"page":"3153-3162","source":"Crossref","is-referenced-by-count":14,"title":["Machine Learning Models for Classification of Cushing's Syndrome Using Retrospective Data"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5497-700X","authenticated-orcid":false,"given":"Senol","family":"Isci","sequence":"first","affiliation":[{"name":"TUBITAK BILGEM Informatics, and Information Security Research Center, Kocaeli, Turkey"}]},{"given":"Derya Sema Yaman","family":"Kalender","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Faculty of Medicine, Izmir Katip Celebi University, Izmir, Turkey"}]},{"given":"Firat","family":"Bayraktar","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Metabolism, Department of Internal Medicine, Dokuz Eylul University Medical School, Izmir, Turkey"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1767-4020","authenticated-orcid":false,"given":"Alper","family":"Yaman","sequence":"additional","affiliation":[{"name":"Department of Biomechatronic Systems, Fraunhofer Institute for Manufacturing Engineering, and Automation IPA Nobelstr. 12, Stuttgart, Germany"}]}],"member":"263","reference":[{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.beem.2012.02.001"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-019-1466-7"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-7-91"},{"key":"ref31","first-page":"431","article-title":"Understanding variable importances in forests of randomized trees","author":"louppe","year":"2013","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.4310\/SII.2009.v2.n3.a8"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1177\/2050312118822912"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0212665"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.4236\/ojs.2013.35043"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1210\/jc.2007-0596"},{"key":"ref11","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"pedregosa","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3171\/2020.3.FOCUS20213"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1373\/clinchem.2018.292201"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2164-9-S1-S23"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3171\/2020.3.FOCUS2060"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1159\/000502211"},{"key":"ref17","first-page":"1","article-title":"A comparison of six methods for missing data imputation","volume":"6","author":"schmitt","year":"2015","journal-title":"Journal of Biometrics & Biostatistics"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s11634-010-0066-3"},{"key":"ref19","first-page":"1547","article-title":"Performance of non-parametric classifiers on highly skewed data","volume":"12","author":"siddiqui","year":"2016","journal-title":"Global Journal of Pure and Applied Mathematics"},{"key":"ref28","first-page":"148","article-title":"Experiments with a new boosting algorithm","volume":"96","author":"freund","year":"1996","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1590\/S0004-27302007000800006"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(14)61375-1"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/BF03343551"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(01)00065-2"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1530\/EJE-13-0702"},{"key":"ref8","first-page":"348","article-title":"Evaluation of endocrine tests. B: Screening for hypercortisolism","volume":"63","author":"holleman","year":"2005","journal-title":"Neth J Med"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1590\/S0004-27302007000800005"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecl.2018.02.001"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1530\/EC-12-0047"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1097\/00000441-191212000-00019"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1080\/10691898.2011.11889611"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"ref21","article-title":"An introduction to the theory of statistics","author":"yule","year":"1950"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/S0895-4356(01)00372-9"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/00031305.1992.10475879","article-title":"An introduction to kernel and nearest-neighbor nonparametric regression","volume":"46","author":"altman","year":"1992","journal-title":"Amer Statist"},{"key":"ref26","author":"breiman","year":"1984","journal-title":"Classification and Regression Trees"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1504\/IJAPR.2016.079733"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/9508208\/09340541.pdf?arnumber=9340541","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T02:31:58Z","timestamp":1724380318000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9340541\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":38,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2021.3054592","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2020.05.31.20118604","asserted-by":"object"}]},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8]]}}}