I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Machine learning for the prediction of sepsis: a systematic..:
Fleuren, Lucas M
;
Klausch, Thomas L. T
;
Zwager, Charlotte L
...
doi:10.17863/CAM.63619. , 2021
Link:
https://doi.org/10.17863/CAM.63619
RT Journal T1
Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy
UL https://suche.suub.uni-bremen.de/peid=base-ftunivcam:oai:www.repository.cam.ac.uk:1810_316511&Exemplar=1&LAN=DE A1 Fleuren, Lucas M A1 Klausch, Thomas L. T A1 Zwager, Charlotte L A1 Schoonmade, Linda J A1 Guo, Tingjie A1 Roggeveen, Luca F A1 Swart, Eleonora L A1 Girbes, Armand R. J A1 Thoral, Patrick A1 Ercole, Ari A1 Hoogendoorn, Mark A1 Elbers, Paul W. G PB Springer Berlin Heidelberg; Intensive Care Medicine YR 2021 K1 Systematic Review K1 Machine learning K1 Sepsis K1 Septic shock K1 Prediction K1 Meta-analysis JF doi:10.17863/CAM.63619 LK http://dx.doi.org/https://doi.org/10.17863/CAM.63619 DO https://doi.org/10.17863/CAM.63619 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)