{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T14:31:49Z","timestamp":1787236309399,"version":"build-2736575974"},"reference-count":35,"publisher":"Elsevier BV","issue":"6","license":[{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"vor","delay-in-days":730,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"funder":[{"name":"Northwell Health"},{"name":"Elmezzi Foundation"}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","jtcvsonline.org","clinicalkey.com.au","clinicalkey.es","clinicalkey.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Thoracic and Cardiovascular Surgery"],"published-print":{"date-parts":[[2021,6]]},"DOI":"10.1016\/j.jtcvs.2020.04.172","type":"journal-article","created":{"date-parts":[[2020,5,29]],"date-time":"2020-05-29T04:09:01Z","timestamp":1590725341000},"page":"1926-1939.e8","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":39,"title":["Using machine learning to predict early readmission following esophagectomy"],"prefix":"10.1016","volume":"161","author":[{"given":"Siavash","family":"Bolourani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad A.","family":"Tayebi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Diao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vihas","family":"Patel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frank","family":"Manetta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul C.","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"Suppl 5","key":"10.1016\/j.jtcvs.2020.04.172_bib1","doi-asserted-by":"crossref","first-page":"S845","DOI":"10.21037\/jtd.2018.12.09","article-title":"Effects of improving outcomes after esophagectomy on the short- and long-term: a review of literature","volume":"11","author":"Fransen","year":"2019","journal-title":"J Thorac Dis"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib2","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.athoracsur.2014.07.052","article-title":"Hospital readmission is associated with poor survival after esophagectomy for esophageal cancer","volume":"99","author":"Fernandez","year":"2015","journal-title":"Ann Thorac Surg"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib3","doi-asserted-by":"crossref","first-page":"5246","DOI":"10.3748\/wjg.v22.i22.5246","article-title":"Post-discharge complications after esophagectomy account for high readmission rates","volume":"22","author":"Chen","year":"2016","journal-title":"World J Gastroenterol"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib4","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1097\/SLA.0000000000001098","article-title":"International consensus on standardization of data collection for complications associated with esophagectomy: esophagectomy complications consensus group (ECCG)","volume":"262","author":"Low","year":"2015","journal-title":"Ann Surg"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib5","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1001\/jamasurg.2018.1645","article-title":"Effect\u00a0of exercise and nutrition prehabilitation on functional capacity in esophagogastric cancer surgery: a randomized clinical trial","volume":"153","author":"Minnella","year":"2018","journal-title":"JAMA Surg"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib6","doi-asserted-by":"crossref","first-page":"2353","DOI":"10.1245\/s10434-014-3612-y","article-title":"Comparison of two preoperative inspiratory muscle training programs to prevent pulmonary complications in patients undergoing esophagectomy: a randomized controlled pilot study","volume":"21","author":"van Adrichem","year":"2014","journal-title":"Ann Surg Oncol"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib7","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1186\/1471-2482-11-2","article-title":"Traditional invasive vs. minimally invasive esophagectomy: a multi-center, randomized trial (TIME-trial)","volume":"11","author":"Biere","year":"2011","journal-title":"BMC Surg"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib8","doi-asserted-by":"crossref","first-page":"3681","DOI":"10.1007\/s00464-016-5406-8","article-title":"Non-inferiority of minimally invasive oesophagectomy: an 8-year retrospective case series","volume":"31","author":"Findlay","year":"2017","journal-title":"Surg Endosc"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib9","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1093\/cid\/cix731","article-title":"Machine learning for healthcare: on the verge of a major shift in healthcare epidemiology","volume":"66","author":"Wiens","year":"2018","journal-title":"Clin Infect Dis"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib11","first-page":"2825","article-title":"Scikit-learn: machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J Machine Learn Res"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib12","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1007\/s11749-016-0481-7","article-title":"A random forest guided tour","volume":"25","author":"Biau","year":"2016","journal-title":"TEST"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib13","author":"Mani"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib15","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1093\/jamiaopen\/ooy012","article-title":"tableone: an open source Python package for producing summary statistics for research papers","volume":"1","author":"Pollard","year":"2018","journal-title":"JAMIA Open"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib16","author":"Salvador"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib17","author":"Wei"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib18","author":"Therneau"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib19","author":"Epskamp"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib20","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.athoracsur.2019.08.035","article-title":"Nationwide analysis of 30-day readmissions following esophagectomy: causes, costs, and risk factors","volume":"109","author":"Goel","year":"2020","journal-title":"Ann Thorac Surg"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib21","first-page":"121","article-title":"Minimally invasive versus open esophagectomy for cancer: a systematic review and meta-analysis","volume":"64","author":"Biere","year":"2009","journal-title":"Minerva Chir"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib22","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1002\/bjs.10728","article-title":"Intrathoracic versus cervical anastomosis and predictors of anastomotic leakage after oesophagectomy for cancer","volume":"105","author":"Gooszen","year":"2018","journal-title":"Br J Surg"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib23","doi-asserted-by":"crossref","first-page":"e021025","DOI":"10.1136\/bmjopen-2017-021025","article-title":"Anastomotic leakage after intrathoracic versus cervical oesophagogastric anastomosis for oesophageal carcinoma in Chinese population: a retrospective cohort study","volume":"8","author":"Liu","year":"2018","journal-title":"BMJ Open"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib24","doi-asserted-by":"crossref","first-page":"922","DOI":"10.1016\/S0003-4975(01)03584-6","article-title":"Pulmonary complications after esophagectomy","volume":"73","author":"Avendano","year":"2002","journal-title":"Ann Thorac Surg"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib25","doi-asserted-by":"crossref","first-page":"2864","DOI":"10.1245\/s10434-019-07478-6","article-title":"Cardiorespiratory comorbidity and postoperative complications following esophagectomy: a European multicenter cohort study","volume":"26","author":"Klevebro","year":"2019","journal-title":"Ann Surg Oncol"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib26","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1016\/j.jgo.2016.07.003","article-title":"Preoperative sarcopenia is a predictor of postoperative pulmonary complications in esophageal cancer following esophagectomy: a retrospective cohort study","volume":"7","author":"Makiura","year":"2016","journal-title":"J Geriatr Oncol"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib27","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.injury.2011.01.004","article-title":"Risk factors that predict mortality in patients with blunt chest wall trauma: a systematic review and meta-analysis","volume":"43","author":"Battle","year":"2012","journal-title":"Injury"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib28","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/s13049-015-0091-5","article-title":"Treatments for blunt chest trauma and their impact on patient outcomes and health service delivery","volume":"23","author":"Unsworth","year":"2015","journal-title":"Scand J Trauma Resusc Emerg Med"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib29","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.1016\/j.suc.2017.06.009","article-title":"Thoracic trauma","volume":"97","author":"Dennis","year":"2017","journal-title":"Surg Clin North Am"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib30","doi-asserted-by":"crossref","first-page":"1155","DOI":"10.1016\/j.athoracsur.2015.05.031","article-title":"Comparison of two national databases for general thoracic surgery","volume":"100","author":"Allen","year":"2015","journal-title":"Ann Thorac Surg"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib31","first-page":"328","article-title":"Machine learning approach for breast cancer prognosis prediction","volume":"11","author":"Filipovic","year":"2020","journal-title":"Comput Model Bioengineer Bioinform"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib32","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.csbj.2014.11.005","article-title":"Machine learning applications in cancer prognosis and prediction","volume":"13","author":"Kourou","year":"2015","journal-title":"Comput Structur Biotechnol J"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib33","first-page":"21371","article-title":"A machine learning approach for early prediction of breast cancer","volume":"6","author":"Malla","year":"2017","journal-title":"Int J Engineer Comput Sci"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib34","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1097\/SHK.0000000000000898","article-title":"Machine learning for predicting outcomes in trauma","volume":"48","author":"Liu","year":"2017","journal-title":"Shock"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib35","doi-asserted-by":"crossref","first-page":"e0169772","DOI":"10.1371\/journal.pone.0169772","article-title":"A comparison of a machine learning model with EuroSCORE II in predicting mortality after elective cardiac surgery: a decision curve analysis","volume":"12","author":"Allyn","year":"2017","journal-title":"PLoS One"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib36","first-page":"137","article-title":"Evaluation of random forest and ensemble methods at predicting complications following cardiac surgery","volume":"11526","author":"Lapp","year":"2019","journal-title":"Artif Intell Med"},{"key":"10.1016\/j.jtcvs.2020.04.172_bib37","doi-asserted-by":"crossref","first-page":"280","DOI":"10.18178\/ijmlc.2018.8.3.700","article-title":"Post-operative life expectancy of lung cancer patients predicted\u00a0by\u00a0Bayesian network model","volume":"8","author":"Sriwong","year":"2018","journal-title":"Int J Machine Learn Comput"}],"updated-by":[{"DOI":"10.1016\/j.jtcvs.2020.07.086","type":"expression_of_concern","label":"Expression of concern","source":"retraction-watch","updated":{"date-parts":[[2020,8,4]],"date-time":"2020-08-04T00:00:00Z","timestamp":1596499200000},"record-id":"24240"},{"DOI":"10.1016\/j.jtcvs.2020.07.086","type":"expression_of_concern","label":"Expression of concern","source":"publisher","updated":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000}},{"DOI":"10.1016\/j.jtcvs.2020.10.002","type":"erratum","label":"Erratum","source":"publisher","updated":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000}}],"container-title":["The Journal of Thoracic and Cardiovascular Surgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0022522320312678?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0022522320312678?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T05:38:27Z","timestamp":1685597907000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0022522320312678"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6]]},"references-count":35,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2021,6]]}},"alternative-id":["S0022522320312678"],"URL":"https:\/\/doi.org\/10.1016\/j.jtcvs.2020.04.172","relation":{},"ISSN":["0022-5223"],"issn-type":[{"value":"0022-5223","type":"print"}],"subject":[],"published":{"date-parts":[[2021,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Using machine learning to predict early readmission following esophagectomy","name":"articletitle","label":"Article Title"},{"value":"The Journal of Thoracic and Cardiovascular Surgery","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jtcvs.2020.04.172","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 by The American Association for Thoracic Surgery","name":"copyright","label":"Copyright"}]}}