Statistically significant feature-based heart murmur detection and classification using spectrogram image comparison of phonocardiogram records with machine learning techniques-Reference-Cited by-同舟云学术

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Statistically significant feature-based heart murmur detection and classification using spectrogram image comparison of phonocardiogram records with machine learning techniques

Published:2024-02-09 Issue:3 Volume:21 Page:243-257
ISSN:1448-837X
Container-title:Australian Journal of Electrical and Electronics Engineering
language:en
Short-container-title:Australian Journal of Electrical and Electronics Engineering

Author:

Careena P.¹²^ORCID,Preetha M. Mary Synthuja Jain¹^ORCID,Arun P.³^ORCID

Affiliation:

1. Department of electronics and communication engineering, Noorul Islam Centre For Higher Education, Tamilnadu, India

2. Department of Electronics and Communication Engineering, Amal Jyothi College of Engineering, Kerala, India

3. Department of Electronics and Communication Engineering, St. Joseph’s College of Engineering and Technology, Kerala, India

Funder

specific grant from any funding

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/1448837X.2024.2312491

Reference32 articles.

1. Transfer Learning Based Heart Valve Disease Classification from Phonocardiogram Signal;Arnab M.;Biomedical Signal Processing and Control,2023

2. Automated detection of heart valve disorders with time-frequency and deep features on PCG signals

3. Detection and Characterization of Bearing Faults from the Frequency Domain Features of Vibration

4. Novel PCG Analysis Method for Discriminating Between Abnormal and Normal Heart Sounds;Badlaoui El O.;IRBM,2019

5. A study of time-frequency features for CNN-based automatic heart sound classification for pathology detection

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