Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, Somnivore(TM), for automated wake–sleep stage classification. We...

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Bibliografiska uppgifter
I publikationen:Front Neurosci
Huvudupphovsmän: Allocca, Giancarlo, Ma, Sherie, Martelli, Davide, Cerri, Matteo, Del Vecchio, Flavia, Bastianini, Stefano, Zoccoli, Giovanna, Amici, Roberto, Morairty, Stephen R., Aulsebrook, Anne E., Blackburn, Shaun, Lesku, John A., Rattenborg, Niels C., Vyssotski, Alexei L., Wams, Emma, Porcheret, Kate, Wulff, Katharina, Foster, Russell, Chan, Julia K. M., Nicholas, Christian L., Freestone, Dean R., Johnston, Leigh A., Gundlach, Andrew L.
Materialtyp: Artigo
Språk:Inglês
Publicerad: Frontiers Media S.A. 2019
Ämnen:
Neuroscience
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC6431640/
https://ncbi.nlm.nih.gov/pubmed/30936820
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2019.00207
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