dc.contributor.author | Mehrjou, Arash | |
dc.contributor.author | Hetzel, Jürgen | |
dc.contributor.author | Schölkopf, Bernhard | |
dc.contributor.author | Bauer, Stefan | |
dc.date.accessioned | 2021-08-31T07:27:14Z | |
dc.date.available | 2021-08-31T07:27:14Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 2041-1723 | |
dc.identifier.uri | http://hdl.handle.net/10900/118366 | |
dc.language.iso | en | de_DE |
dc.publisher | Nature Research | de_DE |
dc.relation.uri | http://dx.doi.org/10.1038/s41467-020-20816-7 | de_DE |
dc.subject.ddc | 500 | de_DE |
dc.title | Real-time prediction of COVID-19 related mortality using electronic health records | de_DE |
dc.type | Article | de_DE |
utue.quellen.id | 20210512015105_00767 | |
utue.personen.roh | Schwab, Patrick | |
utue.personen.roh | Mehrjou, Arash | |
utue.personen.roh | Parbhoo, Sonali | |
utue.personen.roh | Celi, Leo Anthony | |
utue.personen.roh | Hetzel, Jurgen | |
utue.personen.roh | Hofer, Markus | |
utue.personen.roh | Scholkopf, Bernhard | |
utue.personen.roh | Bauer, Stefan | |
dcterms.isPartOf.ZSTitelID | Nature Communications | de_DE |
dcterms.isPartOf.ZS-Issue | Article 1058 | de_DE |
dcterms.isPartOf.ZS-Volume | 12 | de_DE |
utue.fakultaet | 04 Medizinische Fakultät | de_DE |
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