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Historically, sleep stage classification has relied on manual scoring performed by experienced professionals. In recent years, the emergence of machine learning has enabled the automation of this process, thus saving both time and resources. Many of these sleep staging models depend on data which already has been annotated by a professional, but a few try to exploit the vast amount of unlabelled d
