These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

418 related articles for article (PubMed ID: 34202805)

  • 41. Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network.
    Zahid MU; Kiranyaz S; Ince T; Devecioglu OC; Chowdhury MEH; Khandakar A; Tahir A; Gabbouj M
    IEEE Trans Biomed Eng; 2022 Jan; 69(1):119-128. PubMed ID: 34110986
    [TBL] [Abstract][Full Text] [Related]  

  • 42. A deep convolutional neural network model to classify heartbeats.
    Acharya UR; Oh SL; Hagiwara Y; Tan JH; Adam M; Gertych A; Tan RS
    Comput Biol Med; 2017 Oct; 89():389-396. PubMed ID: 28869899
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Lightweight Convolutional Neural Network for Real-Time Arrhythmia Classification on Low-Power Wearable Electrocardiograph.
    Kim S; Chon S; Kim JK; Kim J; Gil Y; Jung S
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1915-1918. PubMed ID: 36085814
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Assessing the Generalizability of a Deep Learning-based Automated Atrial Fibrillation Algorithm.
    Argha A; Li J; Magdy J; Alinejad-Rokny H; Celler BG; Butcher K; Ooi SY; Lovell NH
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-6. PubMed ID: 38082750
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Application of Dense Neural Networks for Detection of Atrial Fibrillation and Ranking of Augmented ECG Feature Set.
    Krasteva V; Christov I; Naydenov S; Stoyanov T; Jekova I
    Sensors (Basel); 2021 Oct; 21(20):. PubMed ID: 34696061
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Detection of arrhythmia in 12-lead varied-length ECG using multi-branch signal fusion network.
    Dong Y; Cai W; Qiu L; Guo Y; Chen Y; Zhang M; Wang D; Zhang H; Wang L
    Physiol Meas; 2022 Oct; 43(10):. PubMed ID: 35705072
    [No Abstract]   [Full Text] [Related]  

  • 47. Recurrence Plot-Based Approach for Cardiac Arrhythmia Classification Using Inception-ResNet-v2.
    Zhang H; Liu C; Zhang Z; Xing Y; Liu X; Dong R; He Y; Xia L; Liu F
    Front Physiol; 2021; 12():648950. PubMed ID: 34079470
    [TBL] [Abstract][Full Text] [Related]  

  • 48. An Improved Convolutional Neural Network Based Approach for Automated Heartbeat Classification.
    Wang H; Shi H; Chen X; Zhao L; Huang Y; Liu C
    J Med Syst; 2019 Dec; 44(2):35. PubMed ID: 31853698
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Review of Deep Learning-Based Atrial Fibrillation Detection Studies.
    Murat F; Sadak F; Yildirim O; Talo M; Murat E; Karabatak M; Demir Y; Tan RS; Acharya UR
    Int J Environ Res Public Health; 2021 Oct; 18(21):. PubMed ID: 34769819
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Transfer Learning in ECG Classification from Human to Horse Using a Novel Parallel Neural Network Architecture.
    Van Steenkiste G; van Loon G; Crevecoeur G
    Sci Rep; 2020 Jan; 10(1):186. PubMed ID: 31932667
    [TBL] [Abstract][Full Text] [Related]  

  • 51. ECG signal classification based on deep CNN and BiLSTM.
    Cheng J; Zou Q; Zhao Y
    BMC Med Inform Decis Mak; 2021 Dec; 21(1):365. PubMed ID: 34963455
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Exploiting exercise electrocardiography to improve early diagnosis of atrial fibrillation with deep learning neural networks.
    Lee HC; Chen CY; Lee SJ; Lee MC; Tsai CY; Chen ST; Li YJ
    Comput Biol Med; 2022 Jul; 146():105584. PubMed ID: 35551013
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Automatic screening method for atrial fibrillation based on lossy compression of the electrocardiogram signal.
    Zhang H; Dong Z; Gao J; Lu P; Wang Z
    Physiol Meas; 2020 Aug; 41(7):075005. PubMed ID: 32464608
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Convolutional neural network for classification of eight types of arrhythmia using 2D time-frequency feature map from standard 12-lead electrocardiogram.
    Jeong DU; Lim KM
    Sci Rep; 2021 Oct; 11(1):20396. PubMed ID: 34650175
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Multi-classification of arrhythmias using a HCRNet on imbalanced ECG datasets.
    Luo X; Yang L; Cai H; Tang R; Chen Y; Li W
    Comput Methods Programs Biomed; 2021 Sep; 208():106258. PubMed ID: 34218172
    [TBL] [Abstract][Full Text] [Related]  

  • 56. WavelNet: A novel convolutional neural network architecture for arrhythmia classification from electrocardiograms.
    Kim N; Seo W; Kim JH; Choi SY; Park SM
    Comput Methods Programs Biomed; 2023 Apr; 231():107375. PubMed ID: 36724593
    [TBL] [Abstract][Full Text] [Related]  

  • 57. A Deep Learning Scheme for Detecting Atrial Fibrillation Based on Fusion of Raw and Discrete Wavelet Transformed ECG Features.
    Rahman MA; Ahmed S; Fattah SA
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1024-1027. PubMed ID: 36086584
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Beatwise ECG Classification for the Detection of Atrial Fibrillation with Deep Learning.
    Yang J; Smaill BH; Gladding P; Zhao J
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083390
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Global ECG Classification by Self-Operational Neural Networks With Feature Injection.
    Zahid MU; Kiranyaz S; Gabbouj M
    IEEE Trans Biomed Eng; 2023 Jan; 70(1):205-215. PubMed ID: 35786545
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records.
    Yildirim O; Talo M; Ciaccio EJ; Tan RS; Acharya UR
    Comput Methods Programs Biomed; 2020 Dec; 197():105740. PubMed ID: 32932129
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 21.