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Journal Abstract Search

133 related items for PubMed ID: 38393859

  • 1. HBNET: A blended ensemble model for the detection of cardiovascular anomalies using phonocardiogram.
    Netto AN, Abraham L, Philip S.
    Technol Health Care; 2024; 32(3):1925-1945. PubMed ID: 38393859
    [Abstract] [Full Text] [Related]

  • 2. Beyond Heart Murmur Detection: Automatic Murmur Grading From Phonocardiogram.
    Elola A, Aramendi E, Oliveira J, Renna F, Coimbra MT, Reyna MA, Sameni R, Clifford GD, Rad AB.
    IEEE J Biomed Health Inform; 2023 Aug; 27(8):3856-3866. PubMed ID: 37163396
    [Abstract] [Full Text] [Related]

  • 3. Classifying Heart Sounds Using Images of Motifs, MFCC and Temporal Features.
    Nogueira DM, Ferreira CA, Gomes EF, Jorge AM.
    J Med Syst; 2019 May 06; 43(6):168. PubMed ID: 31056720
    [Abstract] [Full Text] [Related]

  • 4. Identifying pediatric heart murmurs and distinguishing innocent from pathologic using deep learning.
    Zhou G, Chien C, Chen J, Luan L, Chen Y, Carroll S, Dayton J, Thanjan M, Bayle K, Flynn P.
    Artif Intell Med; 2024 Jul 06; 153():102867. PubMed ID: 38723434
    [Abstract] [Full Text] [Related]

  • 5. Heart Sound Segmentation Using Bidirectional LSTMs With Attention.
    Fernando T, Ghaemmaghami H, Denman S, Sridharan S, Hussain N, Fookes C.
    IEEE J Biomed Health Inform; 2020 Jun 06; 24(6):1601-1609. PubMed ID: 31670683
    [Abstract] [Full Text] [Related]

  • 6. Automated heart sound classification system from unsegmented phonocardiogram (PCG) using deep neural network.
    Krishnan PT, Balasubramanian P, Umapathy S.
    Phys Eng Sci Med; 2020 Jun 06; 43(2):505-515. PubMed ID: 32524434
    [Abstract] [Full Text] [Related]

  • 7. An efficient and robust Phonocardiography (PCG)-based Valvular Heart Diseases (VHD) detection framework using Vision Transformer (ViT).
    Jamil S, Roy AM.
    Comput Biol Med; 2023 May 06; 158():106734. PubMed ID: 36989745
    [Abstract] [Full Text] [Related]

  • 8. An efficient heart murmur recognition and cardiovascular disorders classification system.
    Ahmad MS, Mir J, Ullah MO, Shahid MLUR, Syed MA.
    Australas Phys Eng Sci Med; 2019 Sep 06; 42(3):733-743. PubMed ID: 31313129
    [Abstract] [Full Text] [Related]

  • 9. Analysis of phonocardiogram signals using wavelet transform.
    Meziani F, Debbal SM, Atbi A.
    J Med Eng Technol; 2012 Aug 06; 36(6):283-302. PubMed ID: 22738192
    [Abstract] [Full Text] [Related]

  • 10. Filtering and classification of phonocardiogram signals using wavelet transform.
    Debbal SM, Bereksi-Reguig F.
    J Med Eng Technol; 2008 Aug 06; 32(1):53-65. PubMed ID: 18183520
    [Abstract] [Full Text] [Related]

  • 11. Separation of heart sounds and heart murmurs by Hilbert transform envelogram.
    Atbi A, Debbal SM, Meziani F, Meziane A.
    J Med Eng Technol; 2013 Aug 06; 37(6):375-87. PubMed ID: 23875931
    [Abstract] [Full Text] [Related]

  • 12. Phonocardiogram Signal Processing for Automatic Diagnosis of Congenital Heart Disorders through Fusion of Temporal and Cepstral Features.
    Aziz S, Khan MU, Alhaisoni M, Akram T, Altaf M.
    Sensors (Basel); 2020 Jul 06; 20(13):. PubMed ID: 32640710
    [Abstract] [Full Text] [Related]

  • 13. Unsupervised detection and classification of heartbeats using the dissimilarity matrix in PCG signals.
    Torre-Cruz J, Martinez-Muñoz D, Ruiz-Reyes N, Muñoz-Montoro AJ, Puentes-Chiachio M, Canadas-Quesada FJ.
    Comput Methods Programs Biomed; 2022 Jun 06; 221():106909. PubMed ID: 35649297
    [Abstract] [Full Text] [Related]

  • 14. A computer-aided MFCC-based HMM system for automatic auscultation.
    Chauhan S, Wang P, Sing Lim C, Anantharaman V.
    Comput Biol Med; 2008 Feb 06; 38(2):221-33. PubMed ID: 18045582
    [Abstract] [Full Text] [Related]

  • 15. Convolutional and recurrent neural networks for the detection of valvular heart diseases in phonocardiogram recordings.
    Alkhodari M, Fraiwan L.
    Comput Methods Programs Biomed; 2021 Mar 06; 200():105940. PubMed ID: 33494031
    [Abstract] [Full Text] [Related]

  • 16. Discrete wavelet-aided delineation of PCG signal events via analysis of an area curve length-based decision statistic.
    Homaeinezhad MR, Atyabi SA, Daneshvar E, Ghaffari A, Tahmasebi M.
    Cardiovasc Eng; 2010 Dec 06; 10(4):218-34. PubMed ID: 21181267
    [Abstract] [Full Text] [Related]

  • 17. Detection of valvular heart diseases combining orthogonal non-negative matrix factorization and convolutional neural networks in PCG signals.
    Torre-Cruz J, Canadas-Quesada F, Ruiz-Reyes N, Vera-Candeas P, Garcia-Galan S, Carabias-Orti J, Ranilla J.
    J Biomed Inform; 2023 Sep 06; 145():104475. PubMed ID: 37595770
    [Abstract] [Full Text] [Related]

  • 18. Hybrid Sneaky algorithm-based deep neural networks for Heart sound classification using phonocardiogram.
    Shastri RK, Shastri AR, Nitnaware PP, Padulkar DM.
    Network; 2024 Feb 06; 35(1):1-26. PubMed ID: 38018148
    [Abstract] [Full Text] [Related]

  • 19. Effects of precise cardio sounds on the success rate of phonocardiography.
    Kim Y, Moon M, Moon S, Moon W.
    PLoS One; 2024 Feb 06; 19(7):e0305404. PubMed ID: 39008512
    [Abstract] [Full Text] [Related]

  • 20. A simplicity-based fuzzy clustering approach for detection and extraction of murmurs from the phonocardiogram.
    Nigam V, Priemer R.
    Physiol Meas; 2008 Jan 06; 29(1):33-47. PubMed ID: 18175858
    [Abstract] [Full Text] [Related]

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