A journey toward artificial intelligence-assisted automated sleep scoring.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 35079722.
- Also identified by DOI 10.1016/j.patter.2021.100429 and PMC identifier 8767306.
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Abstract
Sleep scoring is a tedious, time-consuming process that presents a huge challenge in clinics. Leveraging the state-of-the-art U-net architecture, Zhang et al. developed a deep learning algorithm to simultaneously annotate basic and pathologic sleep stages. This model can analyze a full-length sleep record in a few seconds with high accuracy.