| An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction |
| English |
| 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 >] |
| 2019 |
| 1st ed. |
| An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction |
| Cecchini, Vania Filipa  |
| DA NANG PUBLISHING HOUSE |
| 5 |
| Yes |
| International |
| 9781728130026 |
| Da Nang |
| Vietnam |
| 2019 11TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE) |
| from 24-10-2019 to 26-10-2019 |
| IEEE |
| Da Nang City |
| Vietnam |
| [en] metabolic disease ; protein-protein interaction network ; miRNA-target interaction ; machine learning ; disease gene prediction ; imbalanced data |
| Fonds National de la Recherche - FnR |
| http://hdl.handle.net/10993/41512 |
| https://ieeexplore.ieee.org/document/8919337 |
| FnR ; FNR12252781 > Andreas Zilian > DRIVEN > Data-driven Computational Modelling And Applications > 01/09/2018 > 28/02/2025 > 2017 |