Show simple item record

dc.contributor.authorFrancis, N Ken
dc.contributor.authorLuther, Aen
dc.contributor.authorSalib, Een
dc.contributor.authorAllanby, Len
dc.contributor.authorMessenger, Den
dc.contributor.authorAllison, A Sen
dc.contributor.authorSmart, Neil J.en
dc.contributor.authorOckrim, J Ben
dc.date.accessioned2016-03-18T17:37:30Zen
dc.date.available2016-03-18T17:37:30Zen
dc.date.issued2015-07en
dc.identifier.citationThe use of artificial neural networks to predict delayed discharge and readmission in enhanced recovery following laparoscopic colorectal cancer surgery. 2015, 19 (7):419-28 Tech Coloproctolen
dc.identifier.issn1128-045Xen
dc.identifier.pmid26084884en
dc.identifier.doi10.1007/s10151-015-1319-0en
dc.identifier.urihttp://hdl.handle.net/11287/602240en
dc.description.abstractArtificial neural networks (ANNs) can be used to develop predictive tools to enable the clinical decision-making process. This study aimed to investigate the use of an ANN in predicting the outcomes from enhanced recovery after colorectal cancer surgery.en
dc.language.isoenen
dc.publisherSpringeren
dc.relation.urlhttp://dx.doi.org/10.1007/s10151-015-1319-0en
dc.rightsArchived with thanks to Techniques in coloproctologyen
dc.subjectWessex Classification Subject Headings::Gastroenterologyen
dc.titleThe use of artificial neural networks to predict delayed discharge and readmission in enhanced recovery following laparoscopic colorectal cancer surgery.en
dc.typeJournal Articleen
dc.identifier.journalTechniques in coloproctologyen
dc.type.versionPublisheden


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record