BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

422 related articles for article (PubMed ID: 31421606)

  • 1. Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram.
    Erdenebayar U; Kim YJ; Park JU; Joo EY; Lee KJ
    Comput Methods Programs Biomed; 2019 Oct; 180():105001. PubMed ID: 31421606
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Identification of Sleep Apnea Severity Based on Deep Learning from a Short-term Normal ECG.
    Urtnasan E; Park JU; Joo EY; Lee KJ
    J Korean Med Sci; 2020 Dec; 35(47):e399. PubMed ID: 33289367
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Multiclass classification of obstructive sleep apnea/hypopnea based on a convolutional neural network from a single-lead electrocardiogram.
    Urtnasan E; Park JU; Lee KJ
    Physiol Meas; 2018 Jun; 39(6):065003. PubMed ID: 29794342
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Sleep Apnea Detection System Based on a One-Dimensional Deep Convolution Neural Network Model Using Single-Lead Electrocardiogram.
    Chang HY; Yeh CY; Lee CT; Lin CC
    Sensors (Basel); 2020 Jul; 20(15):. PubMed ID: 32722630
    [TBL] [Abstract][Full Text] [Related]  

  • 5. [Sleep apnea automatic detection method based on convolutional neural network].
    Gao Q; Shang L; Wu K
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2021 Aug; 38(4):678-685. PubMed ID: 34459167
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Ensemble of Deep Learning Models for Sleep Apnea Detection: An Experimental Study.
    Mukherjee D; Dhar K; Schwenker F; Sarkar R
    Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34450866
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A Deep Learning Framework for Automatic Sleep Apnea Classification Based on Empirical Mode Decomposition Derived from Single-Lead Electrocardiogram.
    Setiawan F; Lin CW
    Life (Basel); 2022 Sep; 12(10):. PubMed ID: 36294943
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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; 2023():1-4. PubMed ID: 38082822
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Sleep Apnea Prediction Using Deep Learning.
    Wang E; Koprinska I; Jeffries B
    IEEE J Biomed Health Inform; 2023 Nov; 27(11):5644-5654. PubMed ID: 37669207
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic Prediction of Atrial Fibrillation Based on Convolutional Neural Network Using a Short-term Normal Electrocardiogram Signal.
    Erdenebayar U; Kim H; Park JU; Kang D; Lee KJ
    J Korean Med Sci; 2019 Feb; 34(7):e64. PubMed ID: 30804732
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning Approaches to Detect Atrial Fibrillation Using Photoplethysmographic Signals: Algorithms Development Study.
    Kwon S; Hong J; Choi EK; Lee E; Hostallero DE; Kang WJ; Lee B; Jeong ER; Koo BK; Oh S; Yi Y
    JMIR Mhealth Uhealth; 2019 Jun; 7(6):e12770. PubMed ID: 31199302
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Contribution of Different Subbands of ECG in Sleep Apnea Detection Evaluated Using Filter Bank Decomposition and a Convolutional Neural Network.
    Yeh CY; Chang HY; Hu JY; Lin CC
    Sensors (Basel); 2022 Jan; 22(2):. PubMed ID: 35062470
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network.
    Urtnasan E; Park JU; Joo EY; Lee KJ
    J Med Syst; 2018 Apr; 42(6):104. PubMed ID: 29687192
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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(8):1125-1133. PubMed ID: 31482834
    [TBL] [Abstract][Full Text] [Related]  

  • 15. ECG-Derived Heart Rate Variability Interpolation and 1-D Convolutional Neural Networks for Detecting Sleep Apnea.
    Sharan RV; Berkovsky S; Xiong H; Coiera E
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():637-640. PubMed ID: 33018068
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep Learning Forecasts the Occurrence of Sleep Apnea from Single-Lead ECG.
    Bahrami M; Forouzanfar M
    Cardiovasc Eng Technol; 2022 Dec; 13(6):809-815. PubMed ID: 35301676
    [TBL] [Abstract][Full Text] [Related]  

  • 17. SCNN: Scalogram-based convolutional neural network to detect obstructive sleep apnea using single-lead electrocardiogram signals.
    Mashrur FR; Islam MS; Saha DK; Islam SMR; Moni MA
    Comput Biol Med; 2021 Jul; 134():104532. PubMed ID: 34102402
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep Recurrent Neural Networks for Automatic Detection of Sleep Apnea from Single Channel Respiration Signals.
    ElMoaqet H; Eid M; Glos M; Ryalat M; Penzel T
    Sensors (Basel); 2020 Sep; 20(18):. PubMed ID: 32899819
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A RR interval based automated apnea detection approach using residual network.
    Wang L; Lin Y; Wang J
    Comput Methods Programs Biomed; 2019 Jul; 176():93-104. PubMed ID: 31200916
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A Novel Fault Diagnosis Approach for Chillers Based on 1-D Convolutional Neural Network and Gated Recurrent Unit.
    Wang Z; Dong Y; Liu W; Ma Z
    Sensors (Basel); 2020 Apr; 20(9):. PubMed ID: 32357428
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 22.