{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T12:28:47Z","timestamp":1770812927940,"version":"3.50.1"},"reference-count":52,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2018,12,1]],"date-time":"2018-12-01T00:00:00Z","timestamp":1543622400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2018,12,1]],"date-time":"2018-12-01T00:00:00Z","timestamp":1543622400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2019,10,20]],"date-time":"2019-10-20T00:00:00Z","timestamp":1571529600000},"content-version":"am","delay-in-days":323,"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"funder":[{"name":"National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health","award":["K23DK114497"],"award-info":[{"award-number":["K23DK114497"]}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers in Biology and Medicine"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1016\/j.compbiomed.2018.10.017","type":"journal-article","created":{"date-parts":[[2018,10,16]],"date-time":"2018-10-16T12:15:44Z","timestamp":1539692144000},"page":"109-115","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":34,"special_numbering":"C","title":["Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes"],"prefix":"10.1016","volume":"103","author":[{"given":"Dennis H.","family":"Murphree","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elaheh","family":"Arabmakki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Che","family":"Ngufor","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Curtis B.","family":"Storlie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rozalina G.","family":"McCoy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.compbiomed.2018.10.017_bib1","series-title":"Type 2 Diabetes Statistics and Facts","author":"Healthline","year":"2014"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib2","series-title":"National Diabetes Statistics Report","author":"Prevention","year":"2017"},{"issue":"2013","key":"10.1016\/j.compbiomed.2018.10.017_bib3","first-page":"1033","article-title":"Economic costs of diabetes in the U.S.","volume":"36","author":"American Diabetes","year":"2012","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib4","doi-asserted-by":"crossref","first-page":"2478","DOI":"10.2337\/dc07-0499","article-title":"Patient perceptions of quality of life with diabetes-related complications and treatments","volume":"30","author":"Huang","year":"2007","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib5","doi-asserted-by":"crossref","first-page":"1749","DOI":"10.2337\/dc10-2424","article-title":"Correlates of quality of life in older adults with diabetes: the diabetes & aging study","volume":"34","author":"Laiteerapong","year":"2011","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib6","doi-asserted-by":"crossref","first-page":"1761","DOI":"10.2337\/diacare.27.7.1761","article-title":"Tests of glycemia in diabetes","volume":"27","author":"Goldstein","year":"2004","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib7","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.2337\/dc09-9033","article-title":"Expert, International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes","volume":"32","author":"International","year":"2009","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib8","doi-asserted-by":"crossref","first-page":"S55","DOI":"10.2337\/dc18-S006","article-title":"Diabetes, 6. Glycemic targets: standards of medical care in diabetes-2018","volume":"41","author":"American","year":"2018","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib9","doi-asserted-by":"crossref","first-page":"655","DOI":"10.7326\/M17-1362","article-title":"Synopsis of the 2017 U.S. Department of veterans affairs\/U.S. Department of defense clinical practice guideline: management of type 2 diabetes mellitus","volume":"167","author":"Conlin","year":"2017","journal-title":"Ann. Intern. Med."},{"issue":"2015","key":"10.1016\/j.compbiomed.2018.10.017_bib10","doi-asserted-by":"crossref","first-page":"438","DOI":"10.4158\/EP15693.CS","article-title":"AACE\/ACE comprehensive diabetes management algorithm","volume":"21","author":"Garber","year":"2015","journal-title":"Endocr. Pract."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib11","doi-asserted-by":"crossref","first-page":"140","DOI":"10.2337\/dc14-2441","article-title":"Management of hyperglycemia in type 2 diabetes, 2015: a patient-centered approach: update to a position statement of the American Diabetes Association and the European Association for the Study of Diabetes","volume":"38","author":"Inzucchi","year":"2015","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib12","doi-asserted-by":"crossref","first-page":"S73","DOI":"10.2337\/dc18-S008","article-title":"8. Pharmacologic approaches to glycemic treatment: standards of medical care in diabetes-2018","volume":"41","author":"American Diabetes","year":"2018","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib13","doi-asserted-by":"crossref","first-page":"501","DOI":"10.2337\/dc09-1749","article-title":"Secondary failure of metformin monotherapy in clinical practice","volume":"33","author":"Brown","year":"2010","journal-title":"Diabetes Care"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib14","doi-asserted-by":"crossref","first-page":"2127","DOI":"10.1185\/03007995.2010.504396","article-title":"Initial nonadherence, primary failure and therapeutic success of metformin monotherapy in clinical practice","volume":"26","author":"Nichols","year":"2010","journal-title":"Curr. Med. Res. Opin."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib15","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.jdiacomp.2016.07.023","article-title":"Ten-year hemoglobin A1c trajectories and outcomes in type 2 diabetes mellitus: the Diabetes & Aging Study","volume":"31","author":"Laiteerapong","year":"2017","journal-title":"J. Diabet. Complicat."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib16","series-title":"The Elements of Statistical Learning : Data Mining, Inference, and Prediction","author":"Hastie","year":"2009"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib17","first-page":"1751","article-title":"Combining information extraction systems using voting and stacked generalization","volume":"6","author":"Sigletos","year":"2005","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib18","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0893-6080(05)80023-1","article-title":"Stacked generalization","volume":"5","author":"Wolpert","year":"1992","journal-title":"Neural Network."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib19","series-title":"R: a Language and Environment for Statistical Computing","author":"R Core Team","year":"2014"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib20","series-title":"Machine Learning : a Probabilistic Perspective","author":"Murphy","year":"2012"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib21","series-title":"Classification and Regression Training","author":"Kuhn","year":"2014"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib22","unstructured":"Z.A. Deane-Mayer, caretEnsemble."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib23","doi-asserted-by":"crossref","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under 2 or more correlated receiver operating characteristic curves - a nonparametric approach","volume":"44","author":"Delong","year":"1988","journal-title":"Biometrics"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib24","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.ress.2012.11.018","article-title":"Analysis of computationally demanding models with continuous and categorical inputs","volume":"113","author":"Storlie","year":"2013","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib25","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1016\/j.ress.2009.05.007","article-title":"Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models","volume":"94","author":"Storlie","year":"2009","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib26","series-title":"Ebooks Corporation., Global Sensitivity Analysis : the Primer","first-page":"306","author":"Saltelli","year":"2008"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib27","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1111\/dme.12688","article-title":"Predictors of response in initial users of metformin and sulphonylurea derivatives: a systematic review","volume":"32","author":"Martono","year":"2015","journal-title":"Diabet. Med."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib28","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1111\/dme.13154","article-title":"Different clinical prognostic factors are associated with improved glycaemic control: findings from MARCH randomized trial","volume":"34","author":"Han","year":"2017","journal-title":"Diabet. Med."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib29","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.kjms.2012.08.016","article-title":"Comparison of three data mining models for predicting diabetes or prediabetes by risk factors","volume":"29","author":"Meng","year":"2013","journal-title":"Kaohsiung J. Med. Sci."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib30","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1089\/big.2015.0029","article-title":"Type 2 diabetes mellitus trajectories and associated risks","volume":"4","author":"Oh","year":"2016","journal-title":"Big Data"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib31","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1089\/big.2015.0020","article-title":"Population-level prediction of type 2 diabetes from claims data and analysis of risk factors","volume":"3","author":"Razavian","year":"2015","journal-title":"Big Data"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib32","first-page":"885","article-title":"Machine learning approaches for discerning intercorrelation of hematological parameters and glucose level for identification of diabetes mellitus","volume":"12","author":"Worachartcheewan","year":"2013","journal-title":"EXCLI J."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib33","doi-asserted-by":"crossref","first-page":"1328","DOI":"10.1016\/j.compbiomed.2013.07.002","article-title":"Predicting cardiac autonomic neuropathy category for diabetic data with missing values","volume":"43","author":"Abawajy","year":"2013","journal-title":"Comput. Biol. Med."},{"issue":"Suppl 1","key":"10.1016\/j.compbiomed.2018.10.017_bib34","doi-asserted-by":"crossref","first-page":"S5","DOI":"10.1186\/1471-2105-16-S1-S5","article-title":"An interpretable rule-based diagnostic classification of diabetic nephropathy among type 2 diabetes patients","volume":"16","author":"Huang","year":"2015","journal-title":"BMC Bioinf."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib35","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.jdiacomp.2015.03.011","article-title":"Realization of a service for the long-term risk assessment of diabetes-related complications","volume":"29","author":"Lagani","year":"2015","journal-title":"J. Diabet. Complicat."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib36","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1016\/j.jdiacomp.2015.03.001","article-title":"Development and validation of risk assessment models for diabetes-related complications based on the DCCT\/EDIC data","volume":"29","author":"Lagani","year":"2015","journal-title":"J. Diabet. Complicat."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib37","series-title":"Conference Proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual Conference","first-page":"2131","article-title":"Improving risk-stratification of Diabetes complications using temporal data mining","volume":"vol. 2015","author":"Sacchi","year":"2015"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib38","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.phrp.2011.07.005","article-title":"Development of a predictive model for type 2 diabetes mellitus using genetic and clinical data","volume":"2","author":"Lee","year":"2011","journal-title":"Osong Public Health Res Perspect"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib39","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.ygeno.2013.12.007","article-title":"Temporal profiling of cytokine-induced genes in pancreatic beta-cells by meta-analysis and network inference","volume":"103","author":"Lopes","year":"2014","journal-title":"Genomics"},{"issue":"Suppl 2","key":"10.1016\/j.compbiomed.2018.10.017_bib40","doi-asserted-by":"crossref","first-page":"S13","DOI":"10.1186\/1752-0509-5-S2-S13","article-title":"A methodology for multivariate phenotype-based genome-wide association studies to mine pleiotropic genes","volume":"5","author":"Park","year":"2011","journal-title":"BMC Syst. Biol."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib41","doi-asserted-by":"crossref","first-page":"528097","DOI":"10.1155\/2015\/528097","article-title":"Tyrosine kinase ligand-receptor pair prediction by using support vector machine","volume":"2015","author":"Yarimizu","year":"2015","journal-title":"Adv Bioinformatics"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib42","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1089\/big.2013.0019","article-title":"Implications of big data analytics on population health management","volume":"1","author":"Bradley","year":"2013","journal-title":"Big Data"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib43","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/j.compbiomed.2013.02.018","article-title":"Results on mining NHANES data: a case study in evidence-based medicine","volume":"43","author":"Lee","year":"2013","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib44","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.3390\/ijerph110101106","article-title":"On robust methodologies for managing public health care systems","volume":"11","author":"Nimmagadda","year":"2014","journal-title":"Int. J. Environ. Res. Publ. Health"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib45","first-page":"1080","article-title":"The role of the electronic medical record in the assessment of health related quality of life","volume":"2011","author":"Pakhomov","year":"2011","journal-title":"AMIA Annu Symp Proc"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib46","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1186\/1472-6947-11-23","article-title":"An algorithm to identify patients with treated type 2 diabetes using medico-administrative data","volume":"11","author":"Renard","year":"2011","journal-title":"BMC Med. Inf. Decis. Making"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib47","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.csbj.2016.12.005","article-title":"Machine learning and data mining methods in diabetes research","volume":"15","author":"Kavakiotis","year":"2017","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib48","first-page":"1071","article-title":"An efficacy driven approach for medication recommendation in type 2 diabetes treatment using data mining techniques","volume":"192","author":"Liu","year":"2013","journal-title":"Stud. Health Technol. Inf."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib49","doi-asserted-by":"crossref","first-page":"2288","DOI":"10.1056\/NEJMsa1407273","article-title":"Racial and ethnic disparities among enrollees in Medicare Advantage plans","volume":"371","author":"Ayanian","year":"2014","journal-title":"N. Engl. J. Med."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib50","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1186\/1471-2458-5-36","article-title":"Predictors of glycemic control among patients with Type 2 diabetes: a longitudinal study","volume":"5","author":"Benoit","year":"2005","journal-title":"BMC Publ. Health"},{"key":"10.1016\/j.compbiomed.2018.10.017_bib51","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1186\/1472-6963-10-158","article-title":"Changes in glycemic control from 1996 to 2006 among adults with type 2 diabetes: a longitudinal cohort study","volume":"10","author":"Blumenthal","year":"2010","journal-title":"BMC Health Serv. Res."},{"key":"10.1016\/j.compbiomed.2018.10.017_bib52","doi-asserted-by":"crossref","first-page":"386","DOI":"10.2337\/dc07-1934","article-title":"Clinical predictors of disease progression and medication initiation in untreated patients with type 2 diabetes and A1C less than 7%","volume":"31","author":"Pani","year":"2008","journal-title":"Diabetes Care"}],"container-title":["Computers in Biology and Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0010482518303160?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0010482518303160?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,14]],"date-time":"2025-09-14T19:19:32Z","timestamp":1757877572000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/linkinghub.elsevier.com\/retrieve\/pii\/S0010482518303160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":52,"alternative-id":["S0010482518303160"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.compbiomed.2018.10.017","relation":{},"ISSN":["0010-4825"],"issn-type":[{"value":"0010-4825","type":"print"}],"subject":[],"published":{"date-parts":[[2018,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes","name":"articletitle","label":"Article Title"},{"value":"Computers in Biology and Medicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.compbiomed.2018.10.017","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2018 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}]}}