BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

407 related articles for article (PubMed ID: 26987295)

  • 1. ECG feature extraction based on the bandwidth properties of variational mode decomposition.
    Mert A
    Physiol Meas; 2016 Apr; 37(4):530-43. PubMed ID: 26987295
    [TBL] [Abstract][Full Text] [Related]  

  • 2. ECG beat classification using empirical mode decomposition and mixture of features.
    Sahoo S; Mohanty M; Behera S; Sabut SK
    J Med Eng Technol; 2017 Nov; 41(8):652-661. PubMed ID: 29111840
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Classification of myocardial infarction based on hybrid feature extraction and artificial intelligence tools by adopting tunable-Q wavelet transform (TQWT), variational mode decomposition (VMD) and neural networks.
    Zeng W; Yuan J; Yuan C; Wang Q; Liu F; Wang Y
    Artif Intell Med; 2020 Jun; 106():101848. PubMed ID: 32593387
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Electrocardiogram morphological arrhythmia classification using fuzzy entropy-based feature selection and optimal classifier.
    Chaubey K; Saha S
    Biomed Phys Eng Express; 2023 Oct; 9(6):. PubMed ID: 37604128
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Classification of ECG heartbeats using nonlinear decomposition methods and support vector machine.
    Rajesh KNVPS; Dhuli R
    Comput Biol Med; 2017 Aug; 87():271-284. PubMed ID: 28624712
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Developing of robust and high accurate ECG beat classification by combining Gaussian mixtures and wavelets features.
    Alqudah AM; Albadarneh A; Abu-Qasmieh I; Alquran H
    Australas Phys Eng Sci Med; 2019 Mar; 42(1):149-157. PubMed ID: 30644045
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparative study of morphological and time-frequency ECG descriptors for heartbeat classification.
    Christov I; Gómez-Herrero G; Krasteva V; Jekova I; Gotchev A; Egiazarian K
    Med Eng Phys; 2006 Nov; 28(9):876-87. PubMed ID: 16476566
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. The morphological classification of heartbeats as dominant and non-dominant in ECG signals.
    Chiarugi F; Emmanouilidou D; Tsamardinos I
    Physiol Meas; 2010 May; 31(5):611-31. PubMed ID: 20308771
    [TBL] [Abstract][Full Text] [Related]  

  • 11. DE-PNN: Differential Evolution-Based Feature Optimization with Probabilistic Neural Network for Imbalanced Arrhythmia Classification.
    Nasim A; Kim YS
    Sensors (Basel); 2022 Jun; 22(12):. PubMed ID: 35746232
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automatic classification of heartbeats using neural network classifier based on a Bayesian framework.
    Karraz G; Magenes G
    Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():4016-9. PubMed ID: 17946596
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals.
    Elhaj FA; Salim N; Harris AR; Swee TT; Ahmed T
    Comput Methods Programs Biomed; 2016 Apr; 127():52-63. PubMed ID: 27000289
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. 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]  

  • 16. A cascaded classifier for multi-lead ECG based on feature fusion.
    Chen G; Hong Z; Guo Y; Pang C
    Comput Methods Programs Biomed; 2019 Sep; 178():135-143. PubMed ID: 31416542
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automated beat-wise arrhythmia diagnosis using modified U-net on extended electrocardiographic recordings with heterogeneous arrhythmia types.
    Oh SL; Ng EYK; Tan RS; Acharya UR
    Comput Biol Med; 2019 Feb; 105():92-101. PubMed ID: 30599317
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Hybrid Prediction Method for ECG Signals Based on VMD, PSR, and RBF Neural Network.
    Huang F; Qin T; Wang L; Wan H
    Biomed Res Int; 2021; 2021():6624298. PubMed ID: 33816620
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Classification of the electrocardiogram signals using supervised classifiers and efficient features.
    Zadeh AE; Khazaee A; Ranaee V
    Comput Methods Programs Biomed; 2010 Aug; 99(2):179-94. PubMed ID: 20510478
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Detection of Shockable Ventricular Arrhythmia using Variational Mode Decomposition.
    Tripathy RK; Sharma LN; Dandapat S
    J Med Syst; 2016 Apr; 40(4):79. PubMed ID: 26798076
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 21.