Large-scale assessment of consistency in sleep stage scoring rules among multiple sleep centers using an interpretable machine learning algorithm

STUDY OBJECTIVES: Polysomnography is the gold standard in identifying sleep stages; however, there are discrepancies in how technicians use the standards. Because organizing meetings to evaluate this discrepancy and/or reach a consensus among multiple sleep centers is time-consuming, we developed an...

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Gepubliceerd in:J Clin Sleep Med
Hoofdauteurs: Liu, Gi-Ren, Lin, Ting-Yu, Wu, Hau-Tieng, Sheu, Yuan-Chung, Liu, Ching-Lung, Liu, Wen-Te, Yang, Mei-Chen, Ni, Yung-Lun, Chou, Kun-Ta, Chen, Chao-Hsien, Wu, Dean, Lan, Chou-Chin, Chiu, Kuo-Liang, Chiu, Hwa-Yen, Lo, Yu-Lun
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: American Academy of Sleep Medicine 2021
Onderwerpen:
Scientific Investigations
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7853209/
https://ncbi.nlm.nih.gov/pubmed/32964831
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.5664/jcsm.8820
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