暂无分享,去创建一个
Jimeng Sun | Joshua Kulas | Haoqi Sun | Balaji Goparaju | M. Brandon Westover | Siddharth Biswal | Matt T. Bianchi | Jimeng Sun | Haoqi Sun | M. Westover | M. Bianchi | S. Biswal | Joshua A. Kulas | B. Goparaju | Siddharth Biswal | M. Westover
[1] R. Broughton,et al. Sleep patterns in the intensive care unit and on the ward after acute myocardial infarction. , 1978, Electroencephalography and clinical neurophysiology.
[2] D. Thomson,et al. Spectrum estimation and harmonic analysis , 1982, Proceedings of the IEEE.
[3] R. Harrell,et al. Postcardiotomy confusion and sleep loss. , 1987, The Journal of clinical psychiatry.
[4] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.
[5] 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.
[6] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[7] M. Ferraz,et al. Stressors in ICU: perception of the patient, relatives and health care team , 1999, Intensive Care Medicine.
[8] J. Gabor,et al. Sleep disruption in the intensive care unit , 2001, Current opinion in critical care.
[9] Brian Litt,et al. Line length: an efficient feature for seizure onset detection , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[10] T. Guo,et al. The sedative component of anesthesia is mediated by GABAA receptors in an endogenous sleep pathway , 2002, Nature Neuroscience.
[11] A. S. Rodionov,et al. Comparison of linear, nonlinear and feature selection methods for EEG signal classification , 2004, International Conference on Actual Problems of Electron Devices Engineering, 2004. APEDE 2004..
[12] Koen B. E. Böcker,et al. The international 10–20 system revisited: Cartesian and spherical co-ordinates , 2005, Brain Topography.
[13] 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.
[14] D. Hillman,et al. The economic cost of sleep disorders. , 2006, Sleep.
[15] J. Mattout,et al. Automatic analysis of single-channel sleep EEG: validation in healthy individuals. , 2007, Sleep.
[16] Jürgen Schmidhuber,et al. Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks , 2007, NIPS.
[17] Abdulhamit Subasi,et al. EEG signal classification using wavelet feature extraction and a mixture of expert model , 2007, Expert Syst. Appl..
[18] F. Mormann,et al. Seizure prediction: the long and winding road. , 2007, Brain : a journal of neurology.
[19] A. Chesson,et al. The American Academy of Sleep Medicine (AASM) Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications , 2007 .
[20] Suzanne Lesecq,et al. Feature selection for sleep/wake stages classification using data driven methods , 2007, Biomed. Signal Process. Control..
[21] Yann LeCun,et al. Comparing SVM and convolutional networks for epileptic seizure prediction from intracranial EEG , 2008, 2008 IEEE Workshop on Machine Learning for Signal Processing.
[22] P. Anderer,et al. Interrater reliability for sleep scoring according to the Rechtschaffen & Kales and the new AASM standard , 2009, Journal of sleep research.
[23] H. Dickhaus,et al. Classification of Sleep Stages Using Multi-wavelet Time Frequency Entropy and LDA , 2010, Methods of Information in Medicine.
[24] Ali H. Shoeb,et al. Application of Machine Learning To Epileptic Seizure Detection , 2010, ICML.
[25] 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 .
[26] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[27] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[28] V. Ranieri,et al. Sleep disturbances in the critically ill patients: role of delirium and sedative agents. , 2011, Minerva anestesiologica.
[29] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[30] Alex Graves,et al. Generating Sequences With Recurrent Neural Networks , 2013, ArXiv.
[31] Erich Elsen,et al. Deep Speech: Scaling up end-to-end speech recognition , 2014, ArXiv.
[32] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[33] Fei-Fei Li,et al. Large-Scale Video Classification with Convolutional Neural Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[34] D. van Dijk. Long-term cognitive impairment after critical illness. , 2014, The New England journal of medicine.
[35] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[36] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[37] K. Loparo,et al. Evaluation of an automated single-channel sleep staging algorithm , 2015, Nature and science of sleep.
[38] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Mohammed Yeasin,et al. Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks , 2015, ICLR.
[40] Tianqi Chen,et al. XGBoost: A Scalable Tree Boosting System , 2016, KDD.
[41] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Subhashini Venugopalan,et al. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. , 2016, JAMA.
[43] Charles Elkan,et al. Learning to Diagnose with LSTM Recurrent Neural Networks , 2015, ICLR.
[44] Walter F. Stewart,et al. Doctor AI: Predicting Clinical Events via Recurrent Neural Networks , 2015, MLHC.
[45] Jimeng Sun,et al. Using recurrent neural network models for early detection of heart failure onset , 2016, J. Am. Medical Informatics Assoc..
[46] Sebastian Thrun,et al. Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.
[47] Brent Lance,et al. EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces , 2016, Journal of neural engineering.