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 *

182 related articles for article (PubMed ID: 34941897)

  • 1. Expert-enhanced machine learning for cardiac arrhythmia classification.
    Sager S; Bernhardt F; Kehrle F; Merkert M; Potschka A; Meder B; Katus H; Scholz E
    PLoS One; 2021; 16(12):e0261571. PubMed ID: 34941897
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Application of higher order spectra for accurate delineation of atrial arrhythmia.
    Prasad H; Martis RJ; Acharya UR; Min LC; Suri JS
    Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():57-60. PubMed ID: 24109623
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Discriminating atrial flutter from atrial fibrillation using a multilevel model of atrioventricular conduction.
    Scholz EP; Kehrle F; Vossel S; Hess A; Zitron E; Katus HA; Sager S
    Heart Rhythm; 2014 May; 11(5):877-84. PubMed ID: 24561160
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Contemporary Diagnosis and Management of Atrial Flutter: A Continuum of Atrial Fibrillation and Vice Versa?
    Manolis AS
    Cardiol Rev; 2017; 25(6):289-297. PubMed ID: 28832375
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Accurate detection of atrial fibrillation and atrial flutter using the electrocardiomatrix technique.
    Lee V; Xu G; Liu V; Farrehi P; Borjigin J
    J Electrocardiol; 2018; 51(6S):S121-S125. PubMed ID: 30115368
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. 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]  

  • 8. A Meta-Transfer Learning Approach to ECG Arrhythmia Detection.
    Chen W; Banerjee T; John E
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1300-1305. PubMed ID: 36086148
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automatic atrial fibrillation and flutter detection by a handheld ECG recorder, and utility of sequential finger and precordial recordings.
    Brito R; Mondouagne LP; Stettler C; Combescure C; Burri H
    J Electrocardiol; 2018; 51(6):1135-1140. PubMed ID: 30497745
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Cardiac arrhythmia classification using wavelets and Hidden Markov Models - a comparative approach.
    Gomes PR; Soares FO; Correia JH; Lima CS
    Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():4727-30. PubMed ID: 19964839
    [TBL] [Abstract][Full Text] [Related]  

  • 11. P wave detector with PP rhythm tracking: evaluation in different arrhythmia contexts.
    Portet F
    Physiol Meas; 2008 Jan; 29(1):141-55. PubMed ID: 18175865
    [TBL] [Abstract][Full Text] [Related]  

  • 12. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction.
    Attia ZI; Noseworthy PA; Lopez-Jimenez F; Asirvatham SJ; Deshmukh AJ; Gersh BJ; Carter RE; Yao X; Rabinstein AA; Erickson BJ; Kapa S; Friedman PA
    Lancet; 2019 Sep; 394(10201):861-867. PubMed ID: 31378392
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Automatic arrhythmia identification using analysis of the atrioventricular association. Application to a new generation of implantable defibrillators. Participating Centers of the Automatic Recognition of Arrhythmia Study Group.
    Nair M; Saoudi N; Kroiss D; Letac B
    Circulation; 1997 Feb; 95(4):967-73. PubMed ID: 9054759
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Detection of atrial arrhythmia for cardiac rhythm management by implantable devices.
    Morris MM; KenKnight BH; Lang DJ
    J Electrocardiol; 2000; 33 Suppl():133-9. PubMed ID: 11265713
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Robust algorithm for arrhythmia classification in ECG using extreme learning machine.
    Kim J; Shin HS; Shin K; Lee M
    Biomed Eng Online; 2009 Oct; 8():31. PubMed ID: 19863819
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Towards Interpretable Arrhythmia Classification With Human-Machine Collaborative Knowledge Representation.
    Wang J; Li R; Li R; Fu B; Xiao C; Chen DZ
    IEEE Trans Biomed Eng; 2021 Jul; 68(7):2098-2109. PubMed ID: 32946380
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comparison of 24-hour Holter monitoring with 14-day novel adhesive patch electrocardiographic monitoring.
    Barrett PM; Komatireddy R; Haaser S; Topol S; Sheard J; Encinas J; Fought AJ; Topol EJ
    Am J Med; 2014 Jan; 127(1):95.e11-7. PubMed ID: 24384108
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The influence of atrial flutter in automated detection of atrial arrhythmias - are we ready to go into clinical practice?".
    Domazetoski V; Gligoric G; Marinkovic M; Shvilkin A; Krsic J; Kocarev L; Ivanovic MD
    Comput Methods Programs Biomed; 2022 Jun; 221():106901. PubMed ID: 35636359
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A self-adjusting ant colony clustering algorithm for ECG arrhythmia classification based on a correction mechanism.
    Li N; Liu L; Yang Z; Qin S
    Comput Methods Programs Biomed; 2023 Jun; 235():107519. PubMed ID: 37040683
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Demonstration of the potential of white-box machine learning approaches to gain insights from cardiovascular disease electrocardiograms.
    Rieg T; Frick J; Baumgartl H; Buettner R
    PLoS One; 2020; 15(12):e0243615. PubMed ID: 33332440
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.