Do Not Sleep on Linear Models: Simple and Interpretable Techniques Outperform Deep Learning for Sleep Scoring. (arXiv:2207.07753v2 [stat.ML] UPDATED)

Over the last few years, research in automatic sleep scoring has mainly
focused on developing increasingly complex deep learning architectures.
However, recently these approaches achieved only marginal improvements, often
at the expense of requiring more data and more expensive training procedures.
Despite all these efforts and their satisfactory performance, automatic sleep
staging solutions are not widely adopted in a clinical context yet. We argue
that most deep learning solutions for sleep scoring are limited in their
real-world applicability as they …

arxiv deep learning learning linear ml scoring