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Data-driven methodology to predict the ICU length of stay: ..:
Peres, Igor Tona
;
Hamacher, Silvio
;
Cyrino Oliveira, Fernando Luiz
..
Anaesthesia Critical Care & Pain Medicine. 41 (2022) 6 - p. 101142 , 2022
Link:
https://doi.org/10.1016/j.accpm.2022.101142
RT Journal T1
Data-driven methodology to predict the ICU length of stay: A multicentre study of 99,492 admissions in 109 Brazilian units
UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.accpm.2022.101142&Exemplar=1&LAN=DE A1 Peres, Igor Tona A1 Hamacher, Silvio A1 Cyrino Oliveira, Fernando Luiz A1 Bozza, Fernando Augusto A1 Salluh, Jorge Ibrain Figueira PB Elsevier BV YR 2022 SN 2352-5568 JF Anaesthesia Critical Care & Pain Medicine VO 41 IS 6 SP 101142 LK http://dx.doi.org/https://doi.org/10.1016/j.accpm.2022.101142 DO https://doi.org/10.1016/j.accpm.2022.101142 SF ELIB - SuUB Bremen
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