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
Accuracy of Machine Learning Classification Models for the ..:
Olusanya, Micheal O.
;
Ogunsakin, Ropo Ebenezer
;
Ghai, Meenu
.
International Journal of Environmental Research and Public Health. 19 (2022) 21 - p. 14280 , 2022
Link:
https://doi.org/10.3390/ijerph192114280
RT Journal T1
Accuracy of Machine Learning Classification Models for the Prediction of Type 2 Diabetes Mellitus: A Systematic Survey and Meta-Analysis Approach
UL https://suche.suub.uni-bremen.de/peid=cr-10.3390_ijerph192114280&Exemplar=1&LAN=DE A1 Olusanya, Micheal O. A1 Ogunsakin, Ropo Ebenezer A1 Ghai, Meenu A1 Adeleke, Matthew Adekunle PB MDPI AG YR 2022 SN 1660-4601 JF International Journal of Environmental Research and Public Health VO 19 IS 21 SP 14280 LK http://dx.doi.org/https://doi.org/10.3390/ijerph192114280 DO https://doi.org/10.3390/ijerph192114280 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)