{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T09:06:25Z","timestamp":1774515985962,"version":"3.50.1"},"reference-count":24,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100008900","name":"University of South Florida","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008900","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","journalofsurgicalresearch.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Surgical Research"],"published-print":{"date-parts":[[2025,8]]},"DOI":"10.1016\/j.jss.2025.05.014","type":"journal-article","created":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T06:18:19Z","timestamp":1751696299000},"page":"244-251","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Benchmarking Ensemble Models to Predict Prolonged Hospital Stay in Traumatic Brain Injury: A Single-Institution Study"],"prefix":"10.1016","volume":"312","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6180-7778","authenticated-orcid":false,"given":"Shrinit","family":"Babel","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jade","family":"Vanderpool","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maurice","family":"Inkel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandra M.","family":"Farach","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose J.","family":"Diaz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Milad","family":"Behbahaninia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.jss.2025.05.014_bib1","doi-asserted-by":"crossref","first-page":"3055","DOI":"10.3390\/jcm9093055","article-title":"The frequency of, and factors associated with prolonged hospitalization: a multicentre study in victoria, Australia","volume":"9","author":"Ofori-Asenso","year":"2020","journal-title":"J Clin Med"},{"key":"10.1016\/j.jss.2025.05.014_bib2","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1097\/MLR.0000000000001345","article-title":"Predicting patients at risk for prolonged hospital stays","volume":"58","author":"Doctoroff","year":"2020","journal-title":"Med Care"},{"key":"10.1016\/j.jss.2025.05.014_bib3","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.athoracsur.2012.02.010","article-title":"Prolonged stay in intensive care unit is a powerful predictor of adverse outcomes after cardiac operations","volume":"94","author":"Mahesh","year":"2012","journal-title":"Ann Thorac Surg"},{"key":"10.1016\/j.jss.2025.05.014_bib4","doi-asserted-by":"crossref","first-page":"1401","DOI":"10.3390\/jpm13091401","article-title":"Development and validation of an XGBoost-algorithm-powered survival model for predicting in-hospital mortality based on 545,388 isolated severe traumatic brain injury patients from the TQIP database","volume":"13","author":"Cao","year":"2023","journal-title":"J Pers Med"},{"key":"10.1016\/j.jss.2025.05.014_bib5","article-title":"Construction of a predictive model based on MIV-SVR for prognosis and length of stay in patients with traumatic brain injury: retrospective cohort study","volume":"9","author":"Pan","year":"2023","journal-title":"Digit Health"},{"key":"10.1016\/j.jss.2025.05.014_bib6","doi-asserted-by":"crossref","DOI":"10.2196\/41819","article-title":"A machine learning-based approach to predict prognosis and length of hospital stay in adults and children with traumatic brain injury: retrospective cohort study","volume":"24","author":"Fang","year":"2022","journal-title":"J Med Internet Res"},{"key":"10.1016\/j.jss.2025.05.014_bib7","article-title":"Predicting prolonged length of stay in patients with traumatic brain injury: a machine learning approach","volume":"6","author":"Abujaber","year":"2022","journal-title":"Intell-based Med"},{"key":"10.1016\/j.jss.2025.05.014_bib8","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1177\/15533506221139965","article-title":"A pilot machine learning study using trauma admission data to identify risk for high length of stay","volume":"30","author":"Stonko","year":"2023","journal-title":"Surg Innov"},{"key":"10.1016\/j.jss.2025.05.014_bib9","article-title":"Using an artificial neural networks (ANNs) model for prediction of intensive care unit (ICU) outcome and length of stay at hospital in traumatic patients","volume":"9","author":"Gholipour","year":"2015","journal-title":"J Clin Diagn Res"},{"key":"10.1016\/j.jss.2025.05.014_bib10","doi-asserted-by":"crossref","first-page":"5735","DOI":"10.1007\/s00521-017-3242-y","article-title":"Balanced training of a hybrid ensemble method for imbalanced datasets: a case of emergency department readmission prediction","volume":"32","author":"Artetxe","year":"2020","journal-title":"Neural Comput Appl"},{"key":"10.1016\/j.jss.2025.05.014_bib11","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1007\/s10916-017-0789-1","article-title":"Multiclassifier systems for predicting neurological outcome of patients with severe trauma and polytrauma in intensive care units","volume":"41","author":"Gonz\u00e1lez-Robledo","year":"2017","journal-title":"J Med Syst"},{"key":"10.1016\/j.jss.2025.05.014_bib12","doi-asserted-by":"crossref","first-page":"2726","DOI":"10.1038\/s41598-022-06484-1","article-title":"Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine","volume":"12","author":"Guo","year":"2022","journal-title":"Sci Rep"},{"key":"10.1016\/j.jss.2025.05.014_bib13","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1038\/s41597-019-0103-9","article-title":"Multitask learning and benchmarking with clinical time series data","volume":"6","author":"Harutyunyan","year":"2019","journal-title":"Sci Data"},{"key":"10.1016\/j.jss.2025.05.014_bib14","article-title":"Ensemble deep learning: a review","author":"Ganaie","year":"2022","journal-title":"arXiv"},{"key":"10.1016\/j.jss.2025.05.014_bib15","doi-asserted-by":"crossref","first-page":"1808","DOI":"10.3390\/healthcare11121808","article-title":"Ensemble learning for disease prediction: a review","volume":"11","author":"Mahajan","year":"2023","journal-title":"Healthcare"},{"key":"10.1016\/j.jss.2025.05.014_bib16","article-title":"Patient factors associated with prolonged length of stay after traumatic brain injury","volume":"16","author":"Taylor","year":"2024","journal-title":"Cureus"},{"key":"10.1016\/j.jss.2025.05.014_bib17","doi-asserted-by":"crossref","first-page":"956","DOI":"10.1001\/jamasurg.2013.2148","article-title":"Excessively long hospital stays after trauma are not related to the severity of illness: let\u2019s aim to the right target","volume":"148","author":"Hwabejire","year":"2013","journal-title":"JAMA Surg"},{"key":"10.1016\/j.jss.2025.05.014_bib18","article-title":"Towards a systematic approach to design new ensemble learning algorithms","author":"Mendes-Moreira","year":"2024","journal-title":"arXiv"},{"key":"10.1016\/j.jss.2025.05.014_bib19","article-title":"An approach to multiple comparison benchmark evaluations that is stable under manipulation of the comparate set","author":"Ismail-Fawaz","year":"2023","journal-title":"arXiv"},{"key":"10.1016\/j.jss.2025.05.014_bib20","series-title":"2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)","first-page":"1328","article-title":"Threshold based optimization of performance metrics with severely imbalanced Big security data","author":"Calvert","year":"2019"},{"key":"10.1016\/j.jss.2025.05.014_bib21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41746-018-0063-z","article-title":"Reply: metrics to assess machine learning models","volume":"1","author":"Rajkomar","year":"2018","journal-title":"Npj Digit Med"},{"key":"10.1016\/j.jss.2025.05.014_bib22","series-title":"Encyclopedia of Machine Learning and Data Mining","first-page":"314","article-title":"Curse of dimensionality","author":"Keogh","year":"2017"},{"key":"10.1016\/j.jss.2025.05.014_bib23","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1186\/s12911-022-02027-w","article-title":"Evaluation of factors that influenced the length of hospital stay using data mining techniques","volume":"22","author":"Eskandari","year":"2022","journal-title":"BMC Med Inform Decis Mak"},{"key":"10.1016\/j.jss.2025.05.014_bib24","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.jclinepi.2019.02.004","article-title":"A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models","volume":"110","author":"Christodoulou","year":"2019","journal-title":"J Clin Epidemiol"}],"container-title":["Journal of Surgical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0022480425003014?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0022480425003014?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,8,5]],"date-time":"2025-08-05T16:03:07Z","timestamp":1754409787000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0022480425003014"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8]]},"references-count":24,"alternative-id":["S0022480425003014"],"URL":"https:\/\/doi.org\/10.1016\/j.jss.2025.05.014","relation":{},"ISSN":["0022-4804"],"issn-type":[{"value":"0022-4804","type":"print"}],"subject":[],"published":{"date-parts":[[2025,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Benchmarking Ensemble Models to Predict Prolonged Hospital Stay in Traumatic Brain Injury: A Single-Institution Study","name":"articletitle","label":"Article Title"},{"value":"Journal of Surgical Research","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jss.2025.05.014","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Published by Elsevier Inc.","name":"copyright","label":"Copyright"}]}}