Automated sleep staging using sequential XGBoost and multi-scale temporal fusion
Abstract Sleep stage classification is crucial in sleep medicine, but manual scoring is time-consuming, and automated solutions often struggle with complex sleep patterns. This study introduces a novel approach combining multi-scale temporal fusion with sequential XGBoost (eXtreme Gradient Boosting)...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | Discover Artificial Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44163-025-00356-z |
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