Expert-level sleep scoring with deep neural networks
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Haoqi Sun | Balaji Goparaju | M. Brandon Westover | Jimeng Sun | Siddharth Biswal | Matt T. Bianchi | Haoqi Sun | M. Westover | M. Bianchi | Jimeng Sun | S. Biswal | B. Goparaju | Siddharth Biswal | M. Westover
[1] H. Dickhaus,et al. Classification of Sleep Stages Using Multi-wavelet Time Frequency Entropy and LDA , 2010, Methods of Information in Medicine.
[2] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[3] Karim Jerbi,et al. Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines , 2015, Journal of Neuroscience Methods.
[4] V. Kapur,et al. Obstructive sleep apnea devices for out-of-center (OOC) testing: technology evaluation. , 2011, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.
[5] James Reston,et al. Obstructive sleep apnea and risk of motor vehicle crash: systematic review and meta-analysis. , 2009, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.
[6] Fuqiang Chen,et al. Automatic sleep stage classification based on sparse deep belief net and combination of multiple classifiers , 2016 .
[7] Georg Dorffner,et al. Computer-Assisted Automated Scoring of Polysomnograms Using the Somnolyzer System. , 2015, Sleep.
[8] Sheng-Fu Liang,et al. A rule-based automatic sleep staging method , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[9] P. Anderer,et al. Computer-Assisted Sleep Classification according to the Standard of the American Academy of Sleep Medicine : Validation Study of the AASM Version of the Somnolyzer 24 ! 7 , 2010 .
[10] Eleni Giannouli,et al. Performance of a New Portable Wireless Sleep Monitor. , 2017, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.
[11] Olga Sourina,et al. Large-Scale Automated Sleep Staging , 2017, Sleep.
[12] Pooja Budhiraja,et al. Sleep-disordered breathing and cardiovascular disorders. , 2010, Respiratory care.
[13] A. Pack,et al. Performance of an automated polysomnography scoring system versus computer-assisted manual scoring. , 2013, Sleep.
[14] Lars Kai Hansen,et al. Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring , 2017, 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).
[15] Partha P. Mitra,et al. Chronux: A platform for analyzing neural signals , 2010, Journal of Neuroscience Methods.
[16] Subhashini Venugopalan,et al. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. , 2016, JAMA.
[17] D. Léger,et al. Societal costs of insomnia. , 2010, Sleep medicine reviews.
[18] John R. Shambroom,et al. Validation of an automated wireless system to monitor sleep in healthy adults , 2012, Journal of sleep research.
[19] A. Hassan,et al. A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features , 2016, Journal of Neuroscience Methods.
[20] Sebastian Thrun,et al. Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.
[21] J. Mattout,et al. Automatic analysis of single-channel sleep EEG: validation in healthy individuals. , 2007, Sleep.
[22] M. Ohayon,et al. Sleep disorders, medical conditions, and road accident risk. , 2011, Accident; analysis and prevention.
[23] David Watts. Apnea , 1997, The Lancet.
[24] S. Chokroverty,et al. The visual scoring of sleep in adults. , 2007, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.
[25] Lauren E Cipriano,et al. An integrated health-economic analysis of diagnostic and therapeutic strategies in the treatment of moderate-to-severe obstructive sleep apnea. , 2011, Sleep.
[26] David Gozal,et al. The scoring of respiratory events in sleep: reliability and validity. , 2007, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.
[27] Thomas Penzel,et al. Agreement in the scoring of respiratory events and sleep among international sleep centers. , 2013, Sleep.
[28] J. Schoffelen,et al. Comparing spectra and coherences for groups of unequal size , 2007, Journal of Neuroscience Methods.
[29] D. Thomson,et al. Spectrum estimation and harmonic analysis , 1982, Proceedings of the IEEE.
[30] A. Schlögl,et al. An E-Health Solution for Automatic Sleep Classification according to Rechtschaffen and Kales: Validation Study of the Somnolyzer 24 × 7 Utilizing the Siesta Database , 2005, Neuropsychobiology.
[31] M. Younes,et al. Accuracy of Automatic Polysomnography Scoring Using Frontal Electrodes. , 2016, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.
[32] J. Stradling,et al. Obstructive sleep apnoea in adults , 2009, BMJ : British Medical Journal.
[33] A. Muzet,et al. Sleep stage scoring using the neural network model: comparison between visual and automatic analysis in normal subjects and patients. , 1996, Sleep.
[34] Mark J Sculpher,et al. A systematic review of continuous positive airway pressure for obstructive sleep apnoea-hypopnoea syndrome. , 2009, Sleep medicine reviews.
[35] Alex Iranzo,et al. Sleep in Neurodegenerative Diseases. , 2016, Sleep medicine clinics.
[36] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[37] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[38] V. Kapur,et al. Obstructive sleep apnea: diagnosis, epidemiology, and economics. , 2010, Respiratory care.
[39] D. Sclar,et al. Economic Implications of Sleep Disorders , 2012, PharmacoEconomics.
[40] P. Anderer,et al. Interrater reliability for sleep scoring according to the Rechtschaffen & Kales and the new AASM standard , 2009, Journal of sleep research.
[41] K. Loparo,et al. Evaluation of an automated single-channel sleep staging algorithm , 2015, Nature and science of sleep.
[42] Jimeng Sun,et al. Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review , 2018, J. Am. Medical Informatics Assoc..
[43] Ambra Stefani,et al. Validation of a leg movements count and periodic leg movements analysis in a custom polysomnography system , 2017, BMC Neurology.
[44] Matt T Bianchi,et al. Sleep devices: wearables and nearables, informational and interventional, consumer and clinical. , 2017, Metabolism: clinical and experimental.