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Journal Abstract Search

451 related items for PubMed ID: 30445569

  • 1. 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 01; 25(12):1643-1650. PubMed ID: 30445569
    [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 21; 42(11):. PubMed ID: 31289828
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  • 3. 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 19; 16(4):. PubMed ID: 30791379
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  • 4. Tracheal Sound Analysis Using a Deep Neural Network to Detect Sleep Apnea.
    Nakano H, Furukawa T, Tanigawa T.
    J Clin Sleep Med; 2019 Aug 15; 15(8):1125-1133. PubMed ID: 31482834
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  • 5.
    Lux L, Boehlecke B, Lohr KN.
    ; 2004 09 01. PubMed ID: 26065047
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  • 6. Computer-Assisted Automated Scoring of Polysomnograms Using the Somnolyzer System.
    Punjabi NM, Shifa N, Dorffner G, Patil S, Pien G, Aurora RN.
    Sleep; 2015 Oct 01; 38(10):1555-66. PubMed ID: 25902809
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  • 7. 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 15; 22(22):. PubMed ID: 36433422
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  • 8. A multi-task learning model using RR intervals and respiratory effort to assess sleep disordered breathing.
    Xie J, Fonseca P, van Dijk J, Overeem S, Long X.
    Biomed Eng Online; 2024 May 05; 23(1):45. PubMed ID: 38705982
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  • 9. 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 05; 24(7):2073-2081. PubMed ID: 31869808
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  • 10. 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 11; 46(12):. PubMed ID: 37703391
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  • 11. Current hypopnea scoring criteria underscore pediatric sleep disordered breathing.
    Lin CH, Guilleminault C.
    Sleep Med; 2011 Aug 11; 12(7):720-9. PubMed ID: 21700494
    [Abstract] [Full Text] [Related]

  • 12. Performance of an automated polysomnography scoring system versus computer-assisted manual scoring.
    Malhotra A, Younes M, Kuna ST, Benca R, Kushida CA, Walsh J, Hanlon A, Staley B, Pack AI, Pien GW.
    Sleep; 2013 Apr 01; 36(4):573-82. PubMed ID: 23565003
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  • 13. Convolution-and Attention-Based Neural Network for Automated Sleep Stage Classification.
    Zhu T, Luo W, Yu F.
    Int J Environ Res Public Health; 2020 Jun 10; 17(11):. PubMed ID: 32532084
    [Abstract] [Full Text] [Related]

  • 14. Long Short-Term Memory Networks for Unconstrained Sleep Stage Classification Using Polyvinylidene Fluoride Film Sensor.
    Choi SH, Kwon HB, Jin HW, Yoon H, Lee MH, Lee YJ, Park KS.
    IEEE J Biomed Health Inform; 2020 Dec 10; 24(12):3606-3615. PubMed ID: 32149661
    [Abstract] [Full Text] [Related]

  • 15. Polysomnography for Obstructive Sleep Apnea Should Include Arousal-Based Scoring: An American Academy of Sleep Medicine Position Statement.
    Malhotra RK, Kirsch DB, Kristo DA, Olson EJ, Aurora RN, Carden KA, Chervin RD, Martin JL, Ramar K, Rosen CL, Rowley JA, Rosen IM, American Academy of Sleep Medicine Board of Directors.
    J Clin Sleep Med; 2018 Jul 15; 14(7):1245-1247. PubMed ID: 29991439
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  • 16. Discrepancy in polysomnography scoring for a patient with obstructive sleep apnea hypopnea syndrome.
    Suzuki M, Saigusa H, Chiba S, Yagi T, Shibasaki K, Hayashi M, Suzuki M, Moriyama K, Kodera K.
    Tohoku J Exp Med; 2005 Aug 15; 206(4):353-60. PubMed ID: 15997208
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  • 17. Assessment of automated scoring of polysomnographic recordings in a population with suspected sleep-disordered breathing.
    Pittman SD, MacDonald MM, Fogel RB, Malhotra A, Todros K, Levy B, Geva AB, White DP.
    Sleep; 2004 Nov 01; 27(7):1394-403. PubMed ID: 15586793
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  • 18. 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 01; 24(2):581-590. PubMed ID: 31938990
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  • 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 01; 317():61-70. PubMed ID: 30738880
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  • 20. A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.
    Vaquerizo-Villar F, Alvarez D, Gutierrez-Tobal GC, Del Campo F, Gozal D, Kheirandish-Gozal L, Penzel T, Hornero R.
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul 01; 2023():1-4. PubMed ID: 38082822
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