The use of clustering algorithms in critical care research to unravel patient heterogeneity.
| Published in: | Intensive Care Medicine Vol. 45; no. 7; pp. 1025 - 1029 |
|---|---|
| Main Authors: | , , |
| Format: | editorial tables/charts Journal Article |
| Published: |
Springer Nature
Jul2019
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=137338584&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137338584 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03424642 4BC jtl: Intensive Care Medicine issn: 03424642 maglogo: N pubinfo: dt: Jul2019 vid: 45 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137338584 137338584 NLM31062051 137338584 10.1007/s00134-019-05631-z NLM31062051 137338584 ppf: 1025 ppct: 4 formats: tig: atl: The use of clustering algorithms in critical care research to unravel patient heterogeneity. aug: au: Castela Forte, José Perner, Anders van der Horst, Iwan C. C. affil: Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Groningen, The Netherlands sug: subj: Shock, Septic Cluster Analysis Critical Care Clustering Algorithms Echocardiography pubtype: Academic Journal doctype: editorial tables/charts Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|