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
Leveraging Random Forests for Ovarian Cancer Detection and ..:
, In:
2023 7th International Conference on Electronics, Communication and Aerospace Technology (ICECA)
,
Inture, Anvita Reddy
;
Sai Nadh, Boddu Sasi
;
Sha, Akhbar
... - p. 910-915 , 2023
Link:
https://doi.org/10.1109/ICECA58529.2023.10394819
RT T1 <cTitle>2023 7th International Conference on Electronics, Communication and Aerospace Technology (ICECA)</cTitle>: T1 <Title>Leveraging Random Forests for Ovarian Cancer Detection and Precision Prediction</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10394819&Exemplar=1&LAN=DE A1 Inture, Anvita Reddy A1 Sai Nadh, Boddu Sasi A1 Sha, Akhbar A1 Abhishek, S A1 T, Anjali A1 Mullapudi, Taraka Vignesh YR 2023 K1 Training K1 Medical services K1 Predictive models K1 Robustness K1 Random forests K1 Ovarian cancer K1 Testing K1 Machine learning K1 Random Forest K1 Precision-Recall analysis K1 Medical diagnosis K1 Average precision SP 910 OP 915 LK http://dx.doi.org/https://doi.org/10.1109/ICECA58529.2023.10394819 DO https://doi.org/10.1109/ICECA58529.2023.10394819 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
