Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Oct 10, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.0K

Segmentation-free Heart Pathology Detection Using Deep Learning.

Erika Bondareva, Jing Han, William Bradlow

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 11, 2021
    PubMed
    Summary
    This summary is machine-generated.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Ear-Worn Inertial Sensors Can Predict Gait Metrics and Reconstruct Vertical Ground Reaction Force Curves During Running.

    Journal of applied biomechanics·2026
    Same author

    Randomised controlled trial of a very brief nurse-delivered intervention followed by a digital intervention to support medication adherence and reduce blood pressure in people prescribed treatment for hypertension in primary care: protocol for the Programme on Adherence to Medication (PAM) trial.

    NIHR open research·2026
    Same author

    Continuous Mobile Audio Monitoring for Sleep Apnea Detection.

    IEEE journal of biomedical and health informatics·2026
    Same author

    SALTS: Streamlined Adaptive Learning for Sensors Time Series.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same author

    Deep-Learning Based Segmentation of In-Ear Cardiac Sounds.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same author

    Emotion Recognition from Speech Signals by Mel-Spectrogram and a CNN-RNN.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    See all related articles

    This study introduces a novel, segmentation-free method for classifying heart sounds, improving automated cardiovascular diagnosis. The approach enhances precision for normal and murmur heart sounds, showing potential for practical clinical applications.

    Area of Science:

    • Cardiology
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Cardiovascular diseases are a leading global cause of mortality.
    • Heart sound auscultation is crucial for cardiovascular examination but difficult to master.
    • Existing automated methods often fail with noisy signals or high heart rates due to reliance on segmentation.

    Purpose of the Study:

    • To develop a novel segmentation-free heart sound classification method.
    • To improve the accuracy and robustness of automated cardiovascular diagnosis.
    • To enable practical, automatic detection of heart murmurs.

    Main Methods:

    • Applied discrete wavelet transform for signal denoising.
    • Performed feature extraction and reduction.

    More Related Videos

    3D Whole-heart Myocardial Tissue Analysis
    06:53

    3D Whole-heart Myocardial Tissue Analysis

    Published on: April 12, 2017

    8.9K
    Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
    05:32

    Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

    Published on: February 21, 2025

    463

    Related Experiment Videos

    Last Updated: Oct 10, 2025

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    3.0K
    3D Whole-heart Myocardial Tissue Analysis
    06:53

    3D Whole-heart Myocardial Tissue Analysis

    Published on: April 12, 2017

    8.9K
    Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
    05:32

    Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

    Published on: February 21, 2025

    463
  • Utilized Support Vector Machines and Deep Neural Networks for classification.

    • Main Results:

    • Achieved 81% precision for normal and 96% for murmur classes on the PASCAL heart sound dataset.
    • Demonstrated superior performance compared to existing methods.
    • Achieved 92% precision for normal and 86% for murmur in a user-independent setting.

    Conclusions:

    • The proposed segmentation-free method offers superior performance in heart sound classification.
    • The approach shows significant potential for practical, automatic murmur detection.
    • This method addresses limitations of previous techniques, especially in challenging signal conditions.