Research graph
References from A context-aware temporal modeling through unified multi-scale temporal encoding and hierarchical sequence learning for single-channel EEG sleep staging. Local targets link to admitted publications; unresolved targets remain external evidence.
Deep learning and medical diagnosis: A review of literature
10.3390/mti2030047 · 2018 · External reference
Machine-learning-based disease diagnosis: A comprehensive review
10.3390/healthcare10030541 · 2022 · External reference
An explainable deep learning-based method for schizophrenia diagnosis using generative data-augmentation
10.1109/access.2024.3428847 · 2024 · External reference
10.1007/978-3-319-10443-0_39
10.1007/978-3-319-10443-0_39 · External reference
10.1109/isbi.2014.6868045
10.1109/isbi.2014.6868045 · External reference
Sleep: A health imperative
10.5665/sleep.1846 · 2012 · External reference
Short- and long-term health consequences of sleep disruption
10.2147/nss.s134864 · 2017 · External reference
A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects
10.1001/archpsyc.1969.01740140118016 · 1969 · External reference
Subclinical epileptiform activity and sleep disturbances in Alzheimer’s disease
10.1002/brb3.3306 · 2023 · External reference
EEG power spectral analysis of abnormal cortical activations during REM/NREM sleep in obstructive sleep apnea
2021 · External reference
Interrater reliability for sleep scoring according to the Rechtschaffen & Kales and the new AASM standard
10.1111/j.1365-2869.2008.00700.x · 2009 · External reference
The American Academy of Sleep Medicine inter-scorer reliability program: Sleep stage scoring
10.5664/jcsm.2350 · 2013 · External reference
Efficient sleep stage recognition system based on EEG signal using k-means clustering based feature weighting
10.1016/j.eswa.2010.04.043 · 2010 · External reference
Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines
10.1016/j.jneumeth.2015.01.022 · 2015 · External reference
Multi-scale ResNet and BiGRU automatic sleep staging based on attention mechanism
2022 · External reference
AI-Driven sleep staging from actigraphy and heart rate
2023 · External reference
An evaluation of cardiorespiratory and movement features with respect to sleep-stage classification
10.1109/jbhi.2013.2276083 · 2014 · External reference
A novel, fast and efficient single-sensor automatic sleep-stage classification based on complementary cross-frequency coupling estimates
10.1016/j.clinph.2017.12.039 · 2018 · External reference
Analysis and classification of sleep stages based on difference visibility graphs from a single-channel EEG signal
10.1109/jbhi.2014.2303991 · 2014 · External reference
10.1007/978-981-97-8620-6_1
10.1007/978-981-97-8620-6_1 · External reference
Performance enhancement of P300 detection by multiscale-CNN
2021 · External reference
Linking attention-based multiscale CNN with dynamical GCN for driving fatigue detection
2021 · External reference
Subject-specific CNN model with parameter-based transfer learning for SSVEP detection
10.1016/j.bspc.2024.107404 · 2025 · External reference
CBAM-DeepConvNet: Convolutional block attention module-deep convolutional neural network for asymmetric visual evoked potentials recognition
2025 · External reference
An attention-based deep learning approach for sleep stage classification with single-channel EEG
10.1109/tnsre.2021.3076234 · 2021 · External reference
DeepSleepNet: A model for automatic sleep stage scoring based on raw single-channel EEG
10.1109/tnsre.2017.2721116 · 2017 · External reference
SeqSleepNet: End-to-end hierarchical recurrent neural network for sequence-to-sequence automatic sleep staging
10.1109/tnsre.2019.2896659 · 2019 · External reference
SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach
10.1371/journal.pone.0216456 · 2019 · External reference
SleepEGAN: A GAN-enhanced ensemble deep learning model for imbalanced classification of sleep stages
10.1016/j.bspc.2024.106020 · 2024 · External reference
Analysis of a sleep-dependent neuronal feedback loop: The slow-wave microcontinuity of the EEG
10.1109/10.867928 · 2000 · External reference
Training with noise is equivalent to Tikhonov regularization
10.1162/neco.1995.7.1.108 · 1995 · External reference
Joint classification and prediction CNN framework for automatic sleep stage classification
10.1109/tbme.2018.2872652 · 2019 · External reference
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10.1109/cvpr.2018.00745
10.1109/cvpr.2018.00745 · External reference
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Attention-based models for speech recognition
2015 · External reference
U-time: A fully convolutional network for time series segmentation applied to sleep staging
2019 · External reference
Temporal focal modulation networks for sleep stage scoring
10.1007/s10044-025-01475-0 · 2025 · External reference
SleepGCN: A transition rule learning model based on Graph Convolutional Network for sleep staging
10.1016/j.cmpb.2024.108405 · 2024 · External reference
XSleepNet: Multi-view sequential model for automatic sleep staging
2022 · External reference
Physiology of sleep
10.2337/diaspect.29.1.5 · 2016 · External reference
Age-related modifications of NREM sleep EEG: From childhood to middle age
10.1046/j.1365-2869.2001.00252.x · 2001 · External reference
Week-by-week changes in sleep EEG in healthy full-term newborns
10.1093/sleep/zsz261 · 2020 · External reference
Automatic sleep staging of EEG signals: Recent development, challenges, and future directions
10.1088/1361-6579/ac6049 · 2022 · External reference
Automated sleep staging in epilepsy using deep learning on standard electroencephalogram and wearable data
10.1111/jsr.70061 · 2025 · External reference
Automatic sleep staging: Recent advances and perspectives
2022 · External reference
A comparison of manual and automated sleep staging
2013 · External reference
Machine learning approaches for sleep staging: A systematic review
2019 · External reference
Quasi-supervised classification of sleep stages using single-channel EEG
2015 · External reference
