Paper published in a book (Scientific congresses, symposiums and conference proceedings)
An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction
Cecchini, Vania Filipa; Nguyen, Thanh-Phuong; Pfau, Thomas et al.
2019In Cecchini, Vania Filipa (Ed.) An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction
Peer reviewed
 

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Keywords :
metabolic disease; protein-protein interaction network; miRNA-target interaction; machine learning; disease gene prediction; imbalanced data
Disciplines :
Computer science
Author, co-author :
Cecchini, Vania Filipa ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Nguyen, Thanh-Phuong ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Pfau, Thomas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
De Landtsheer, Sébastien ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Sauter, Thomas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
External co-authors :
no
Language :
English
Title :
An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction
Publication date :
2019
Event name :
2019 11TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE)
Event organizer :
IEEE
Event place :
Da Nang City, Vietnam
Event date :
from 24-10-2019 to 26-10-2019
Audience :
International
Main work title :
An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction
Author, co-author :
Publisher :
DA NANG PUBLISHING HOUSE, Da Nang, Vietnam
Edition :
1st ed.
ISBN/EAN :
9781728130026
Pages :
5
Peer reviewed :
Peer reviewed
Focus Area :
Systems Biomedicine
FnR Project :
FNR12252781 - Data-driven Computational Modelling And Applications, 2017 (01/09/2018-28/02/2025) - Andreas Zilian
Funders :
FNR - Fonds National de la Recherche [LU]
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since 13 January 2020

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