Weak self-supervised learning for seizure forecasting: a feasibility study
This paper proposes an artificial intelligence system that continuously improves over time at event prediction using initially unlabelled data by using self-supervised learning. Time-series data are inherently autocorrelated. By using a detection model to generate weak labels on the fly, which are c...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The Royal Society
2022-08-01
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| Series: | Royal Society Open Science |
| Subjects: | |
| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.220374 |