133 related articles for article (PubMed ID: 37703391)
1. Standardized image-based polysomnography database and deep learning algorithm for sleep-stage classification.
Jeong J; Yoon W; Lee JG; Kim D; Woo Y; Kim DK; Shin HW
Sleep; 2023 Dec; 46(12):. PubMed ID: 37703391
[TBL] [Abstract][Full Text] [Related]
2. Automated sleep stage scoring of the Sleep Heart Health Study using deep neural networks.
Zhang L; Fabbri D; Upender R; Kent D
Sleep; 2019 Oct; 42(11):. PubMed ID: 31289828
[TBL] [Abstract][Full Text] [Related]
3. Expert-level sleep scoring with deep neural networks.
Biswal S; Sun H; Goparaju B; Westover MB; Sun J; Bianchi MT
J Am Med Inform Assoc; 2018 Dec; 25(12):1643-1650. PubMed ID: 30445569
[TBL] [Abstract][Full Text] [Related]
4. Inter-database validation of a deep learning approach for automatic sleep scoring.
Alvarez-Estevez D; Rijsman RM
PLoS One; 2021; 16(8):e0256111. PubMed ID: 34398931
[TBL] [Abstract][Full Text] [Related]
5. A Deep Learning Model for Automated Sleep Stages Classification Using PSG Signals.
Yildirim O; Baloglu UB; Acharya UR
Int J Environ Res Public Health; 2019 Feb; 16(4):. PubMed ID: 30791379
[TBL] [Abstract][Full Text] [Related]
6. Automated multi-model deep neural network for sleep stage scoring with unfiltered clinical data.
Zhang X; Xu M; Li Y; Su M; Xu Z; Wang C; Kang D; Li H; Mu X; Ding X; Xu W; Wang X; Han D
Sleep Breath; 2020 Jun; 24(2):581-590. PubMed ID: 31938990
[TBL] [Abstract][Full Text] [Related]
7. Accurate Deep Learning-Based Sleep Staging in a Clinical Population With Suspected Obstructive Sleep Apnea.
Korkalainen H; Aakko J; Nikkonen S; Kainulainen S; Leino A; Duce B; Afara IO; Myllymaa S; Toyras J; Leppanen T
IEEE J Biomed Health Inform; 2020 Jul; 24(7):2073-2081. PubMed ID: 31869808
[TBL] [Abstract][Full Text] [Related]
8. An automated heart rate-based algorithm for sleep stage classification: Validation using conventional polysomnography and an innovative wearable electrocardiogram device.
Pini N; Ong JL; Yilmaz G; Chee NIYN; Siting Z; Awasthi A; Biju S; Kishan K; Patanaik A; Fifer WP; Lucchini M
Front Neurosci; 2022; 16():974192. PubMed ID: 36278001
[TBL] [Abstract][Full Text] [Related]
9. Expert-level automated sleep staging of long-term scalp electroencephalography recordings using deep learning.
Abou Jaoude M; Sun H; Pellerin KR; Pavlova M; Sarkis RA; Cash SS; Westover MB; Lam AD
Sleep; 2020 Nov; 43(11):. PubMed ID: 32478820
[TBL] [Abstract][Full Text] [Related]
10. Validation Study on Automated Sleep Stage Scoring Using a Deep Learning Algorithm.
Cho JH; Choi JH; Moon JE; Lee YJ; Lee HD; Ha TK
Medicina (Kaunas); 2022 Jun; 58(6):. PubMed ID: 35744042
[No Abstract] [Full Text] [Related]
11. A Deep Transfer Learning Framework for Sleep Stage Classification with Single-Channel EEG Signals.
ElMoaqet H; Eid M; Ryalat M; Penzel T
Sensors (Basel); 2022 Nov; 22(22):. PubMed ID: 36433422
[TBL] [Abstract][Full Text] [Related]
12. Deep learning-based sleep stage classification with cardiorespiratory and body movement activities in individuals with suspected sleep disorders.
Morokuma S; Hayashi T; Kanegae M; Mizukami Y; Asano S; Kimura I; Tateizumi Y; Ueno H; Ikeda S; Niizeki K
Sci Rep; 2023 Oct; 13(1):17730. PubMed ID: 37853134
[TBL] [Abstract][Full Text] [Related]
13. Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters.
Stepnowsky C; Levendowski D; Popovic D; Ayappa I; Rapoport DM
Sleep Med; 2013 Nov; 14(11):1199-207. PubMed ID: 24047533
[TBL] [Abstract][Full Text] [Related]
14. Automatic sleep scoring: A deep learning architecture for multi-modality time series.
Yan R; Li F; Zhou DD; Ristaniemi T; Cong F
J Neurosci Methods; 2021 Jan; 348():108971. PubMed ID: 33160019
[TBL] [Abstract][Full Text] [Related]
15. Automatic sleep scoring with LSTM networks: impact of time granularity and input signals.
Tăuțan AM; Rossi AC; Ionescu B
Biomed Tech (Berl); 2022 Aug; 67(4):267-281. PubMed ID: 35660133
[TBL] [Abstract][Full Text] [Related]
16. [Study on the method of polysomnography sleep stage staging based on attention mechanism and bidirectional gate recurrent unit].
Liu Y; He C; Yuan C; Zhang H; Ji C
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2023 Feb; 40(1):35-43. PubMed ID: 36854546
[TBL] [Abstract][Full Text] [Related]
17. Automatic sleep staging for the young and the old - Evaluating age bias in deep learning.
Baumert M; Hartmann S; Phan H
Sleep Med; 2023 Jul; 107():18-25. PubMed ID: 37099916
[TBL] [Abstract][Full Text] [Related]
18. An End-to-End Multi-Channel Convolutional Bi-LSTM Network for Automatic Sleep Stage Detection.
Toma TI; Choi S
Sensors (Basel); 2023 May; 23(10):. PubMed ID: 37430865
[TBL] [Abstract][Full Text] [Related]
19. Iterative expert-in-the-loop classification of sleep PSG recordings using a hierarchical clustering.
Gerla V; Kremen V; Macas M; Dudysova D; Mladek A; Sos P; Lhotska L
J Neurosci Methods; 2019 Apr; 317():61-70. PubMed ID: 30738880
[TBL] [Abstract][Full Text] [Related]
20.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Next] [New Search]