{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T22:08:38Z","timestamp":1777586918675,"version":"3.51.4"},"reference-count":32,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T00:00:00Z","timestamp":1770422400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2020-04382"],"award-info":[{"award-number":["RGPIN-2020-04382"]}],"id":[{"id":"10.13039\/501100000038","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":["Computers in Biology and Medicine"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.compbiomed.2026.111546","type":"journal-article","created":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T02:18:47Z","timestamp":1771035527000},"page":"111546","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Unsupervised identification of sepsis subpopulations in the eICU database: A multi-method clustering approach with validation"],"prefix":"10.1016","volume":"204","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-3748-5489","authenticated-orcid":false,"given":"Hanwen","family":"Ju","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9863-7752","authenticated-orcid":false,"given":"Joel A.","family":"Dubin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"4","key":"10.1016\/j.compbiomed.2026.111546_bib0005","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1002\/wics.101","article-title":"Principal component analysis","volume":"2","author":"Abdi","year":"2010","journal-title":"Wiley Interdiscip. Rev.: Comput. Stat."},{"issue":"8","key":"10.1016\/j.compbiomed.2026.111546_bib0010","doi-asserted-by":"crossref","first-page":"2316","DOI":"10.1097\/CCM.0b013e3181810378","article-title":"Glucose variability and mortality in patients with sepsis","volume":"36","author":"Ali","year":"2008","journal-title":"Crit. Care Med."},{"issue":"1","key":"10.1016\/j.compbiomed.2026.111546_bib0015","first-page":"1","article-title":"A dendrite method for cluster analysis","volume":"3","author":"Cali\u0144ski","year":"1974","journal-title":"Commun. Stat.-Theory Methods"},{"key":"10.1016\/j.compbiomed.2026.111546_bib0020","article-title":"Fdapace: Functional Data Analysis and Empirical Dynamics","volume":"6","author":"Carroll","year":"2021"},{"issue":"4","key":"10.1016\/j.compbiomed.2026.111546_bib0025","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.3390\/jcm12041499","article-title":"Identification of distinct clinical phenotypes of heterogeneous mechanically ventilated ICU patients using cluster analysis","volume":"12","author":"Chen","year":"2023","journal-title":"J. Clin. Med."},{"issue":"2","key":"10.1016\/j.compbiomed.2026.111546_bib0030","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1109\/TPAMI.1979.4766909","article-title":"A cluster separation measure","volume":"PAMI-1","author":"Davies","year":"2009","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"8","key":"10.1016\/j.compbiomed.2026.111546_bib0035","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1177\/000313480807400802","article-title":"Blood glucose variability is associated with mortality in the surgical intensive care unit","volume":"74","author":"Dossett","year":"2008","journal-title":"Am. Surg."},{"issue":"5","key":"10.1016\/j.compbiomed.2026.111546_bib0040","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1097\/SHK.0000000000000234","article-title":"Persistent lymphopenia after diagnosis of sepsis predicts mortality","volume":"42","author":"Drewry","year":"2014","journal-title":"Shock"},{"key":"10.1016\/j.compbiomed.2026.111546_bib0045","series-title":"KDD","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"vol. 96","author":"Ester","year":"1996"},{"issue":"9","key":"10.1016\/j.compbiomed.2026.111546_bib0050","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pdig.0000598","article-title":"Short-term vital parameter forecasting in the intensive care unit: a benchmark study leveraging data from patients after cardiothoracic surgery","volume":"3","author":"Hinrichs","year":"2024","journal-title":"PLOS Digit. Health"},{"issue":"3","key":"10.1016\/j.compbiomed.2026.111546_bib0055","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/S1473-3099(13)70001-X","article-title":"Immunosuppression in sepsis: a novel understanding of the disorder and a new therapeutic approach","volume":"13","author":"Hotchkiss","year":"2013","journal-title":"Lancet Infect. Dis."},{"issue":"5","key":"10.1016\/j.compbiomed.2026.111546_bib0060","doi-asserted-by":"crossref","first-page":"1949","DOI":"10.1007\/s40121-022-00684-y","article-title":"Application of machine learning for clinical subphenotype identification in sepsis","volume":"11","author":"Hu","year":"2022","journal-title":"Infect. Dis. Ther."},{"issue":"1","key":"10.1016\/j.compbiomed.2026.111546_bib0065","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/sdata.2016.35","article-title":"Mimic-iii, a freely accessible critical care database","volume":"3","author":"Johnson","year":"2016","journal-title":"Sci. Data"},{"issue":"4","key":"10.1016\/j.compbiomed.2026.111546_bib0070","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1002\/ehf2.12471","article-title":"Blood urea nitrogen variation upon admission and at discharge in patients with heart failure","volume":"6","author":"Khoury","year":"2019","journal-title":"ESC Heart Fail."},{"key":"10.1016\/j.compbiomed.2026.111546_bib0075","author":"Kingma"},{"issue":"1","key":"10.1016\/j.compbiomed.2026.111546_bib0080","doi-asserted-by":"crossref","first-page":"5416","DOI":"10.1038\/s41467-019-13056-x","article-title":"The art of using t-sne for single-cell transcriptomics","volume":"10","author":"Kobak","year":"2019","journal-title":"Nat. Commun."},{"issue":"9","key":"10.1016\/j.compbiomed.2026.111546_bib0085","doi-asserted-by":"crossref","first-page":"1464","DOI":"10.1109\/5.58325","article-title":"The self-organizing map","volume":"78","author":"Kohonen","year":"1990","journal-title":"Proc. IEEE"},{"key":"10.1016\/j.compbiomed.2026.111546_bib0090","series-title":"Self-Organizing Maps","volume":"vol. 30","author":"Kohonen","year":"2012"},{"key":"10.1016\/j.compbiomed.2026.111546_bib0095","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13054-019-2372-2","article-title":"Heterogeneity in sepsis: new biological evidence with clinical applications","volume":"23","author":"Leligdowicz","year":"2019","journal-title":"Crit. Care."},{"key":"10.1016\/j.compbiomed.2026.111546_bib0100","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13054-021-03734-y","article-title":"Identification of distinct clinical phenotypes of acute respiratory distress syndrome with differential responses to treatment","volume":"25","author":"Liu","year":"2021","journal-title":"Crit. Care."},{"key":"10.1016\/j.compbiomed.2026.111546_bib0105","author":"McInnes"},{"issue":"1","key":"10.1016\/j.compbiomed.2026.111546_bib0110","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/sdata.2018.178","article-title":"The eicu collaborative research database, a freely available multi-center database for critical care research","volume":"5","author":"Pollard","year":"2018","journal-title":"Sci. Data"},{"key":"10.1016\/j.compbiomed.2026.111546_bib0115","article-title":"Exploratory analysis of electronic intensive care unit (eicu) database","author":"Rajabalizadeh","year":"2020","journal-title":"medRxiv"},{"key":"10.1016\/j.compbiomed.2026.111546_bib0120","series-title":"2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)","first-page":"747","article-title":"Cluster quality analysis using silhouette score","author":"Shahapure","year":"2020"},{"key":"10.1016\/j.compbiomed.2026.111546_bib0125","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2020.104182","article-title":"Identifying subpopulations of septic patients: a temporal data-driven approach","volume":"130","author":"Sharafoddini","year":"2021","journal-title":"Comput. Biol. Med."},{"issue":"2","key":"10.1016\/j.compbiomed.2026.111546_bib0130","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1210\/er.2009-0021","article-title":"Glucose variability; does it matter?","volume":"31","author":"Siegelaar","year":"2010","journal-title":"Endocr. Rev."},{"key":"10.1016\/j.compbiomed.2026.111546_bib0135","first-page":"1","article-title":"Mice: multivariate imputation by chained equations in r","volume":"45","author":"Van Buuren","year":"2011","journal-title":"J. Stat. Softw."},{"issue":"11","key":"10.1016\/j.compbiomed.2026.111546_bib0140","article-title":"Visualizing data using t-sne","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"issue":"10","key":"10.1016\/j.compbiomed.2026.111546_bib0145","doi-asserted-by":"crossref","first-page":"e2","DOI":"10.23915\/distill.00002","article-title":"How to use t-sne effectively","volume":"1","author":"Wattenberg","year":"2016","journal-title":"Distill"},{"issue":"1","key":"10.1016\/j.compbiomed.2026.111546_bib0150","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1186\/s13054-022-04071-4","article-title":"Sepsis subphenotyping based on organ dysfunction trajectory","volume":"26","author":"Xu","year":"2022","journal-title":"Crit. Care."},{"issue":"470","key":"10.1016\/j.compbiomed.2026.111546_bib0155","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1198\/016214504000001745","article-title":"Functional data analysis for sparse longitudinal data","volume":"100","author":"Yao","year":"2005","journal-title":"J. Am. Stat. Assoc."},{"issue":"5","key":"10.1016\/j.compbiomed.2026.111546_bib0160","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1097\/01.CCM.0000215112.84523.F0","article-title":"Acute physiology and chronic health evaluation (apache) IV: hospital mortality assessment for today\u2019s critically ill patients","volume":"34","author":"Zimmerman","year":"2006","journal-title":"Crit. Care Med."}],"container-title":["Computers in Biology and Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0010482526001083?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0010482526001083?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T20:09:22Z","timestamp":1777406962000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0010482526001083"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":32,"alternative-id":["S0010482526001083"],"URL":"https:\/\/doi.org\/10.1016\/j.compbiomed.2026.111546","relation":{},"ISSN":["0010-4825"],"issn-type":[{"value":"0010-4825","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Unsupervised identification of sepsis subpopulations in the eICU database: A multi-method clustering approach with validation","name":"articletitle","label":"Article Title"},{"value":"Computers in Biology and Medicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compbiomed.2026.111546","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"111546"}}