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Do not sleep on traditional machine learning Simple and interpretable techniques are competitive to deep learning for sleep scoring
dc.contributor.author | Van Der Donckt, Jeroen | |
dc.contributor.author | Van Der Donckt, Jonas | |
dc.contributor.author | Deprost, Emiel | |
dc.contributor.author | Vandenbussche, Nicolas | |
dc.contributor.author | Rademaker, Michael | |
dc.contributor.author | Vandewiele, Gilles | |
dc.contributor.author | Van Hoecke, Sofie | |
dc.date.accessioned | 2023-01-12T03:13:12Z | |
dc.date.available | 2023-01-12T03:13:12Z | |
dc.date.issued | 2023-MAR | |
dc.identifier.issn | 1746-8094 | |
dc.identifier.other | WOS:000898625200003 | |
dc.identifier.uri | https://imec-publications.be/handle/20.500.12860/40962 | |
dc.source | WOS | |
dc.title | Do not sleep on traditional machine learning Simple and interpretable techniques are competitive to deep learning for sleep scoring | |
dc.type | Journal article | |
dc.identifier.doi | 10.1016/j.bspc.2022.104429 | |
dc.source.numberofpages | 9 | |
dc.source.peerreview | yes | |
dc.source.journal | BIOMEDICAL SIGNAL PROCESSING AND CONTROL | |
dc.source.volume | 81 | |
imec.availability | Under review |
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