BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

249 related articles for article (PubMed ID: 27318329)

  • 1. Proposition of novel classification approach and features for improved real-time arrhythmia monitoring.
    Kim YJ; Heo J; Park KS; Kim S
    Comput Biol Med; 2016 Aug; 75():190-202. PubMed ID: 27318329
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal.
    Asl BM; Setarehdan SK; Mohebbi M
    Artif Intell Med; 2008 Sep; 44(1):51-64. PubMed ID: 18585905
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier.
    Alickovic E; Subasi A
    J Med Syst; 2016 Apr; 40(4):108. PubMed ID: 26922592
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Heartbeat classification using morphological and dynamic features of ECG signals.
    Ye C; Kumar BV; Coimbra MT
    IEEE Trans Biomed Eng; 2012 Oct; 59(10):2930-41. PubMed ID: 22907960
    [TBL] [Abstract][Full Text] [Related]  

  • 5. [Arrhythmia heartbeats classification based on neighborhood preserving embedding algorithm].
    Gao X; Li Z; Chen S; Li J
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2017 Feb; 34(1):1-6. PubMed ID: 29717579
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Ensemble classifier fostered detection of arrhythmia using ECG data.
    Ramkumar M; Alagarsamy M; Balakumar A; Pradeep S
    Med Biol Eng Comput; 2023 Sep; 61(9):2453-2466. PubMed ID: 37145258
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Cardiac arrhythmia beat classification using DOST and PSO tuned SVM.
    Raj S; Ray KC; Shankar O
    Comput Methods Programs Biomed; 2016 Nov; 136():163-77. PubMed ID: 27686713
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Block-based neural networks for personalized ECG signal classification.
    Jiang W; Kong SG
    IEEE Trans Neural Netw; 2007 Nov; 18(6):1750-61. PubMed ID: 18051190
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Arrhythmia Classification of ECG Signals Using Hybrid Features.
    Anwar SM; Gul M; Majid M; Alnowami M
    Comput Math Methods Med; 2018; 2018():1380348. PubMed ID: 30538768
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Automated Method for Discrimination of Arrhythmias Using Time, Frequency, and Nonlinear Features of Electrocardiogram Signals.
    Hajeb-Mohammadalipour S; Ahmadi M; Shahghadami R; Chon KH
    Sensors (Basel); 2018 Jun; 18(7):. PubMed ID: 29966276
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients.
    Kutlu Y; Kuntalp D
    Comput Methods Programs Biomed; 2012 Mar; 105(3):257-67. PubMed ID: 22055998
    [TBL] [Abstract][Full Text] [Related]  

  • 13. High efficient system for automatic classification of the electrocardiogram beats.
    Zadeh AE; Khazaee A
    Ann Biomed Eng; 2011 Mar; 39(3):996-1011. PubMed ID: 21140292
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.
    Li H; Yuan D; Wang Y; Cui D; Cao L
    Sensors (Basel); 2016 Oct; 16(10):. PubMed ID: 27775596
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automatic recognition of arrhythmia based on principal component analysis network and linear support vector machine.
    Yang W; Si Y; Wang D; Guo B
    Comput Biol Med; 2018 Oct; 101():22-32. PubMed ID: 30098452
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Arrhythmia Recognition and Classification Using ECG Morphology and Segment Feature Analysis.
    Zhu W; Chen X; Wang Y; Wang L
    IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(1):131-138. PubMed ID: 29994263
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automated detection of shockable and non-shockable arrhythmia using novel wavelet-based ECG features.
    Sharma M; Singh S; Kumar A; San Tan R; Acharya UR
    Comput Biol Med; 2019 Dec; 115():103446. PubMed ID: 31627019
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Novel Approach for Multi-Lead ECG Classification Using DL-CCANet and TL-CCANet.
    Yang W; Si Y; Wang D; Zhang G
    Sensors (Basel); 2019 Jul; 19(14):. PubMed ID: 31330925
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection.
    Park J; Kang M; Gao J; Kim Y; Kang K
    J Med Syst; 2017 Jan; 41(1):11. PubMed ID: 27889872
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comparison of real-time classification systems for arrhythmia detection on Android-based mobile devices.
    Leutheuser H; Gradl S; Kugler P; Anneken L; Arnold M; Achenbach S; Eskofier BM
    Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():2690-3. PubMed ID: 25570545
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.