{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T10:35:28Z","timestamp":1793010928895,"version":"4.5.0"},"reference-count":23,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T00:00:00Z","timestamp":1779753600000},"content-version":"vor","delay-in-days":145,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008465","name":"Catherine D Sharpe Charitable Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008465","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Brain and Spine"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1016\/j.bas.2026.106108","type":"journal-article","created":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T23:50:53Z","timestamp":1779839453000},"page":"106108","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Development and validation of a machine learning model utilizing the ACS-NSQIP database for predicting early postoperative Re-operation in lumbar microdiscectomy"],"prefix":"10.1016","volume":"6","author":[{"given":"Mert Marcel","family":"Dagli","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaskeerat","family":"Gujral","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Connor A.","family":"Wathen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yohannes","family":"Ghenbot","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John D.","family":"Arena","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua L.","family":"Golubovsky","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6152-2510","authenticated-orcid":false,"given":"Hasan S.","family":"Ahmad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elie","family":"Massaad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Shin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jang W.","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali K.","family":"Ozturk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William C.","family":"Welch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.bas.2026.106108_bib1","series-title":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"2623","article-title":"A next-generation hyperparameter optimization framework","author":"Akiba","year":"2019"},{"key":"10.1016\/j.bas.2026.106108_bib2","doi-asserted-by":"crossref","first-page":"S114","DOI":"10.1093\/neuros\/nyw066","article-title":"Prevention of surgical site infection in spine surgery","volume":"80","author":"Anderson","year":"2017","journal-title":"Neurosurgery"},{"key":"10.1016\/j.bas.2026.106108_bib3","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J. Artif. Intell. Res."},{"key":"10.1016\/j.bas.2026.106108_bib4","doi-asserted-by":"crossref","first-page":"5197","DOI":"10.2147\/IDR.S417431","article-title":"Using machine learning to predict surgical site infection after lumbar spine surgery","volume":"16","author":"Chen","year":"2023","journal-title":"Infect. Drug Resist."},{"key":"10.1016\/j.bas.2026.106108_bib5","doi-asserted-by":"crossref","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"key":"10.1016\/j.bas.2026.106108_bib6","doi-asserted-by":"crossref","first-page":"1980","DOI":"10.1177\/00031348211065101","article-title":"The use of artificial intelligence and machine learning in surgery: a comprehensive literature review","volume":"89","author":"Dagli","year":"2023","journal-title":"Am. Surg."},{"key":"10.1016\/j.bas.2026.106108_bib7","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.wneu.2015.05.059","article-title":"Risk factors for surgical site infection after spinal surgery: a meta-analysis","volume":"95","author":"Fei","year":"2016","journal-title":"World Neurosurg."},{"key":"10.1016\/j.bas.2026.106108_bib8","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1613\/jair.1.11192","article-title":"SMOTE for learning from imbalanced data: progress and challenges, marking the 15-year anniversary","volume":"61","author":"Fern\u00e1ndez","year":"2018","journal-title":"J. Artif. Intell. Res."},{"key":"10.1016\/j.bas.2026.106108_bib9","doi-asserted-by":"crossref","first-page":"399","DOI":"10.3171\/2019.9.SPINE19860","article-title":"Using machine learning to predict 30-day readmissions after posterior lumbar fusion: an NSQIP study involving 23,264 patients","volume":"32","author":"Hopkins","year":"2020","journal-title":"J. Neurosurg. Spine"},{"key":"10.1016\/j.bas.2026.106108_bib10","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1016\/j.spinee.2018.11.013","article-title":"Prediction of mechanical complications in adult spinal deformity surgery-the GAP score versus the schwab classification","volume":"19","author":"Jacobs","year":"2019","journal-title":"Spine J."},{"key":"10.1016\/j.bas.2026.106108_bib11","doi-asserted-by":"crossref","first-page":"686","DOI":"10.14245\/ns.1938414.207","article-title":"Artificial intelligence for adult spinal deformity","volume":"16","author":"Joshi","year":"2019","journal-title":"Neurospine"},{"key":"10.1016\/j.bas.2026.106108_bib12","doi-asserted-by":"crossref","first-page":"762","DOI":"10.1016\/j.jspd.2018.03.003","article-title":"Predicting surgical complications in patients undergoing elective adult spinal deformity procedures using machine learning","volume":"6","author":"Kim","year":"2018","journal-title":"Spine Deform."},{"key":"10.1016\/j.bas.2026.106108_bib13","first-page":"149","article-title":"Risk factors for surgical site infection in spinal surgery","volume":"98","author":"Olsen","year":"2003","journal-title":"J. Neurosurg."},{"key":"10.1016\/j.bas.2026.106108_bib14","doi-asserted-by":"crossref","first-page":"e318","DOI":"10.1016\/j.wneu.2018.11.158","article-title":"Risk factors for surgical site infection after spinal surgery: a systematic review and meta-analysis based on twenty-seven studies","volume":"123","author":"Peng","year":"2019","journal-title":"World Neurosurg."},{"key":"10.1016\/j.bas.2026.106108_bib15","doi-asserted-by":"crossref","DOI":"10.1177\/03000605241293696","article-title":"Can machine learning models improve the prediction of surgical site infection in abdominal surgery than traditional statistical models?","volume":"52","author":"Piebpien","year":"2024","journal-title":"J. Int. Med. Res."},{"key":"10.1016\/j.bas.2026.106108_bib17","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1097\/BRS.0b013e3181bcde61","article-title":"The presentation, incidence, etiology, and treatment of surgical site infections after spinal surgery","volume":"35","author":"Pull ter Gunne","year":"2010","journal-title":"Spine"},{"key":"10.1016\/j.bas.2026.106108_bib16","doi-asserted-by":"crossref","first-page":"1422","DOI":"10.1097\/BRS.0b013e3181a03013","article-title":"Incidence, prevalence, and analysis of risk factors for surgical site infection following adult spinal surgery","volume":"34","author":"Pull ter Gunne","year":"2009","journal-title":"Spine"},{"key":"10.1016\/j.bas.2026.106108_bib18","doi-asserted-by":"crossref","first-page":"736","DOI":"10.3171\/2016.10.SPINE16197","article-title":"Development of a preoperative predictive model for major complications following adult spinal deformity surgery","volume":"26","author":"Scheer","year":"2017","journal-title":"J. Neurosurg. Spine"},{"key":"10.1016\/j.bas.2026.106108_bib19","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2021.103456","article-title":"hyOPTXg: OPTUNA hyper-parameter optimization framework for predicting cardiovascular disease using XGBoost","volume":"73","author":"Srinivas","year":"2022","journal-title":"Biomed. Signal Process Control"},{"key":"10.1016\/j.bas.2026.106108_bib20","doi-asserted-by":"crossref","first-page":"E7","DOI":"10.3171\/2019.5.FOCUS19241","article-title":"Machine learning applications for the prediction of surgical site infection in neurological operations","volume":"47","author":"Tunthanathip","year":"2019","journal-title":"Neurosurg. Focus"},{"key":"10.1016\/j.bas.2026.106108_bib21","doi-asserted-by":"crossref","first-page":"135","DOI":"10.25259\/SNI_178_2025","article-title":"Toward transparency: implications and future directions of artificial intelligence prediction model reporting in healthcare","volume":"16","author":"Turlip","year":"2025","journal-title":"Surg. Neurol. Int."},{"key":"10.1016\/j.bas.2026.106108_bib22","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1136\/bmj.39335.541782.AD","article-title":"Strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies","volume":"335","author":"von Elm","year":"2007","journal-title":"BMJ"},{"key":"10.1016\/j.bas.2026.106108_bib23","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1097\/BRS.0000000000003218","article-title":"Incidence of surgical site infection after spine surgery: a systematic review and meta-analysis","volume":"45","author":"Zhou","year":"2020","journal-title":"Spine"}],"container-title":["Brain and Spine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2772529426001840?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2772529426001840?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T10:12:22Z","timestamp":1793009542000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2772529426001840"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":23,"alternative-id":["S2772529426001840"],"URL":"https:\/\/doi.org\/10.1016\/j.bas.2026.106108","relation":{},"ISSN":["2772-5294"],"issn-type":[{"value":"2772-5294","type":"print"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Development and validation of a machine learning model utilizing the ACS-NSQIP database for predicting early postoperative Re-operation in lumbar microdiscectomy","name":"articletitle","label":"Article Title"},{"value":"Brain and Spine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bas.2026.106108","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier B.V. on behalf of EANS, the European Association of Neurosurgical Societies, EUROSPINE, the Spine Society of Europe.","name":"copyright","label":"Copyright"}],"article-number":"106108"}}