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Pubmed for Handhelds

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Journal Abstract Search

176 related items for PubMed ID: 38931636

  • 1. Machine Learning Algorithms for Processing and Classifying Unsegmented Phonocardiographic Signals: An Efficient Edge Computing Solution Suitable for Wearable Devices.
    De Fazio R, Spongano L, De Vittorio M, Patrono L, Visconti P.
    Sensors (Basel); 2024 Jun 14; 24(12):. PubMed ID: 38931636
    [Abstract] [Full Text] [Related]

  • 2. Automatic heart sound classification from segmented/unsegmented phonocardiogram signals using time and frequency features.
    Khan FA, Abid A, Khan MS.
    Physiol Meas; 2020 Jun 03; 41(5):055006. PubMed ID: 32259811
    [Abstract] [Full Text] [Related]

  • 3. Phonocardiogram signal analysis for classification of Coronary Artery Diseases using MFCC and 1D adaptive local ternary patterns.
    Iqtidar K, Qamar U, Aziz S, Khan MU.
    Comput Biol Med; 2021 Nov 03; 138():104926. PubMed ID: 34656868
    [Abstract] [Full Text] [Related]

  • 4. 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 03; 42(3):733-743. PubMed ID: 31313129
    [Abstract] [Full Text] [Related]

  • 5. 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 03; 158():106734. PubMed ID: 36989745
    [Abstract] [Full Text] [Related]

  • 6. 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]

  • 7. A comparative study of the SVM and K-nn machine learning algorithms for the diagnosis of respiratory pathologies using pulmonary acoustic signals.
    Palaniappan R, Sundaraj K, Sundaraj S.
    BMC Bioinformatics; 2014 Jun 27; 15():223. PubMed ID: 24970564
    [Abstract] [Full Text] [Related]

  • 8. 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 27; 43(2):505-515. PubMed ID: 32524434
    [Abstract] [Full Text] [Related]

  • 9. 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]

  • 10. A multi-scale and multi-domain heart sound feature-based machine learning model for ACC/AHA heart failure stage classification.
    Zheng Y, Guo X, Wang Y, Qin J, Lv F.
    Physiol Meas; 2022 Jun 28; 43(6):. PubMed ID: 35512699
    [Abstract] [Full Text] [Related]

  • 11. Human respiration monitoring using infrared thermography and artificial intelligence.
    Jagadev P, Giri LI.
    Biomed Phys Eng Express; 2020 Mar 13; 6(3):035007. PubMed ID: 33438652
    [Abstract] [Full Text] [Related]

  • 12. Analysis of phonocardiogram signals through proactive denoising using novel self-discriminant learner.
    Puri C, Singh R, Bandyopadhyay S, Ukil A, Mukherjee A.
    Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul 13; 2017():2753-2756. PubMed ID: 29060468
    [Abstract] [Full Text] [Related]

  • 13. Diagnosis of cardiac abnormalities based on phonocardiogram using a novel fuzzy matching feature extraction method.
    Yang W, Xu J, Xiang J, Yan Z, Zhou H, Wen B, Kong H, Zhu R, Li W.
    BMC Med Inform Decis Mak; 2022 Sep 02; 22(1):230. PubMed ID: 36056352
    [Abstract] [Full Text] [Related]

  • 14. Towards classifying non-segmented heart sound records using instantaneous frequency based features.
    Alqudah AM.
    J Med Eng Technol; 2019 Oct 02; 43(7):418-430. PubMed ID: 31769312
    [Abstract] [Full Text] [Related]

  • 15. A novel heart sound segmentation algorithm via multi-feature input and neural network with attention mechanism.
    Guo Y, Yang H, Guo T, Pan J, Wang W.
    Biomed Phys Eng Express; 2022 Dec 30; 9(1):. PubMed ID: 36301698
    [Abstract] [Full Text] [Related]

  • 16. Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers.
    Deist TM, Dankers FJWM, Valdes G, Wijsman R, Hsu IC, Oberije C, Lustberg T, van Soest J, Hoebers F, Jochems A, El Naqa I, Wee L, Morin O, Raleigh DR, Bots W, Kaanders JH, Belderbos J, Kwint M, Solberg T, Monshouwer R, Bussink J, Dekker A, Lambin P.
    Med Phys; 2018 Jul 30; 45(7):3449-3459. PubMed ID: 29763967
    [Abstract] [Full Text] [Related]

  • 17. Evaluation of feature extraction techniques and classifiers for finger movement recognition using surface electromyography signal.
    Phukpattaranont P, Thongpanja S, Anam K, Al-Jumaily A, Limsakul C.
    Med Biol Eng Comput; 2018 Dec 30; 56(12):2259-2271. PubMed ID: 29911250
    [Abstract] [Full Text] [Related]

  • 18. 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 30; 200():105940. PubMed ID: 33494031
    [Abstract] [Full Text] [Related]

  • 19. Deep learning based classification of unsegmented phonocardiogram spectrograms leveraging transfer learning.
    Khan KN, Khan FA, Abid A, Olmez T, Dokur Z, Khandakar A, Chowdhury MEH, Khan MS.
    Physiol Meas; 2021 Sep 27; 42(9):. PubMed ID: 34388736
    [Abstract] [Full Text] [Related]

  • 20. Towards an Efficient One-Class Classifier for Mobile Devices and Wearable Sensors on the Context of Personal Risk Detection.
    Trejo LA, Barrera-Animas AY.
    Sensors (Basel); 2018 Aug 30; 18(9):. PubMed ID: 30200188
    [Abstract] [Full Text] [Related]

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