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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Bibliographic Details
Main Authors: Jiří Kuchyňka, Oldřich Vyšata
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Discover Artificial Intelligence
Subjects:
Online Access:https://doi.org/10.1007/s44163-025-00356-z
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