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1 Ergebnisse
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An interpretable machine learning model for predicting 28-d..:
Wen, Chengli
;
Zhang, Xu
;
Li, Yong
...
PLOS ONE. 19 (2024) 5 - p. e0303469 , 2024
Link:
https://doi.org/10.1371/journal.pone.0303469
RT Journal T1
An interpretable machine learning model for predicting 28-day mortality in patients with sepsis-associated liver injury
UL https://suche.suub.uni-bremen.de/peid=cr-10.1371_journal.pone.0303469&Exemplar=1&LAN=DE A1 Wen, Chengli A1 Zhang, Xu A1 Li, Yong A1 Xiao, Wanmeng A1 Hu, Qinxue A1 Lei, Xianying A1 Xu, Tao A1 Liang, Sicheng A1 Gao, Xiaolan A1 Zhang, Chao A1 Yu, Zehui A1 Lü, Muhan A1 Aunsri, Nattapol PB Public Library of Science (PLoS) YR 2024 SN 1932-6203 JF PLOS ONE VO 19 IS 5 SP e0303469 LK http://dx.doi.org/https://doi.org/10.1371/journal.pone.0303469 DO https://doi.org/10.1371/journal.pone.0303469 SF ELIB - SuUB Bremen
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