dc.contributor.author | Vollmer, Michael | |
dc.date.accessioned | 2024-06-04T09:48:42Z | |
dc.date.available | 2024-06-04T09:48:42Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 2405-8440 | |
dc.identifier.uri | http://hdl.handle.net/10900/154014 | |
dc.language.iso | en | de_DE |
dc.publisher | Cambridge : Cell Press | de_DE |
dc.relation.uri | http://dx.doi.org/10.1016/j.heliyon.2023.e20752 | de_DE |
dc.subject.ddc | 500 | de_DE |
dc.title | Performance of artificial intelligence-based algorithms to predict prolonged length of stay after head and neck cancer surgery | de_DE |
dc.type | Article | de_DE |
utue.quellen.id | 20240124000000_00591 | |
utue.personen.roh | Vollmer, Andreas | |
utue.personen.roh | Nagler, Simon | |
utue.personen.roh | Horner, Marius | |
utue.personen.roh | Hartmann, Stefan | |
utue.personen.roh | Brands, Roman C. | |
utue.personen.roh | Breitenbuecher, Niko | |
utue.personen.roh | Straub, Anton | |
utue.personen.roh | Kuebler, Alexander | |
utue.personen.roh | Vollmer, Michael | |
utue.personen.roh | Gubik, Sebastian | |
utue.personen.roh | Lang, Gernot | |
utue.personen.roh | Wollborn, Jakob | |
utue.personen.roh | Saravi, Babak | |
dcterms.isPartOf.ZSTitelID | Heliyon | de_DE |
dcterms.isPartOf.ZS-Issue | Article e20752 | de_DE |
dcterms.isPartOf.ZS-Volume | 9 (11) | de_DE |
utue.fakultaet | 04 Medizinische Fakultät | de_DE |
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