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| dc.contributor.author | Zeng, Wenhuan | |
| dc.contributor.author | Gautam, Anupam | |
| dc.contributor.author | Huson, Daniel | |
| dc.date.accessioned | 2021-06-23T15:06:10Z | |
| dc.date.available | 2021-06-23T15:06:10Z | |
| dc.date.issued | 2021-01-07 | |
| dc.identifier.uri | http://hdl.handle.net/10900/116443 | |
| dc.language.iso | en | de_DE |
| dc.publisher | MDPI | de_DE |
| dc.relation.uri | http://dx.doi.org/10.3390/computation9010004 | de_DE |
| dc.subject.ddc | 004 | de_DE |
| dc.title | On the Application of Advanced Machine Learning Methods to Analyze Enhanced, Multimodal Data from Persons Infected with COVID-19 | de_DE |
| dc.type | Article | de_DE |
| utue.publikation.seiten | 4 | de_DE |
| utue.personen.roh | Zeng, Wenhuan | |
| utue.personen.roh | Gautam, Anupam | |
| utue.personen.roh | Huson, Daniel H. | |
| dcterms.isPartOf.ZSTitelID | Computation | de_DE |
| dcterms.isPartOf.ZS-Issue | 1 | de_DE |
| dcterms.isPartOf.ZS-Volume | 9 | de_DE |
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