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
Identifying Patient Populations in Texts Describing Drug Ap..:
Gendrin, Aline
;
Souliotis, Leonidas
;
Loudon-Griffiths, James
...
JMIR Formative Research. 7 (2023) - p. e44876 , 2023
Link:
https://doi.org/10.2196/44876
RT Journal T1
Identifying Patient Populations in Texts Describing Drug Approvals Through Deep Learning–Based Information Extraction: Development of a Natural Language Processing Algorithm
UL https://suche.suub.uni-bremen.de/peid=cr-10.2196_44876&Exemplar=1&LAN=DE A1 Gendrin, Aline A1 Souliotis, Leonidas A1 Loudon-Griffiths, James A1 Aggarwal, Ravisha A1 Amoako, Daniel A1 Desouza, Gregory A1 Dimitrievska, Sashka A1 Metcalfe, Paul A1 Louvet, Emilie A1 Sahni, Harpreet PB JMIR Publications Inc. YR 2023 SN 2561-326X JF JMIR Formative Research VO 7 SP e44876 LK http://dx.doi.org/https://doi.org/10.2196/44876 DO https://doi.org/10.2196/44876 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)