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Machine learning approach for automated predicting of COVID..:
Jahangirimehr, Azam
;
Abdolahi Shahvali, Elham
;
Rezaeijo, Seyed Masoud
...
Clinical Nutrition ESPEN. 51 (2022) - p. 404-411 , 2022
Link:
https://doi.org/10.1016/j.clnesp.2022.07.011
RT Journal T1
Machine learning approach for automated predicting of COVID-19 severity based on clinical and paraclinical characteristics: Serum levels of zinc, calcium, and vitamin D
UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.clnesp.2022.07.011&Exemplar=1&LAN=DE A1 Jahangirimehr, Azam A1 Abdolahi Shahvali, Elham A1 Rezaeijo, Seyed Masoud A1 Khalighi, Azam A1 Honarmandpour, Azam A1 Honarmandpour, Fateme A1 Labibzadeh, Mostafa A1 Bahmanyari, Nasrin A1 Heydarheydari, Sahel PB Elsevier BV YR 2022 SN 2405-4577 JF Clinical Nutrition ESPEN VO 51 SP 404 OP 411 LK http://dx.doi.org/https://doi.org/10.1016/j.clnesp.2022.07.011 DO https://doi.org/10.1016/j.clnesp.2022.07.011 SF ELIB - SuUB Bremen
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