Reducing False Alarm Rates in Neonatal Intensive Care: A New Machine Learning Approach
| dc.contributor.author | Ostojic, D. | |
| dc.contributor.author | Guglielmini, S. | |
| dc.contributor.author | Moser, V. | |
| dc.contributor.author | Fauchere, J. C. | |
| dc.contributor.author | Bucher, H. U. | |
| dc.contributor.author | Bassler, D. | |
| dc.contributor.author | et al. | |
| dc.date.accessioned | 2021-12-13T16:32:04Z | |
| dc.date.available | 2021-12-13T16:32:04Z | |
| dc.date.issued | 2020 | |
| dc.identifier.citation | in Oxygen Transport to Tissue Xli. vol. 1232 (Issue), P. D. Ryu, J. C. LaManna, D. K. Harrison, and S. S. Lee, Eds., ed Cham: Springer International Publishing Ag, 2020, pp. 285-290. | |
| dc.identifier.uri | https://yoda.csem.ch/handle/20.500.12839/402 | |
| dc.title | Reducing False Alarm Rates in Neonatal Intensive Care: A New Machine Learning Approach | |
| dc.type | Proceedings Article | |
| dc.type.csemdivisions | Div-M | |
| dc.type.csemresearchareas | Digital Health |
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