Automated Acute Myocardial Infarction Detection Using Machine Learning From Phonocardiogram

Automated Acute Myocardial Infarction Detection Using Machine Learning From Phonocardiogram

Early detection of myocardial infarction (MI) is critical due to rapid heart muscle deterioration. Current diagnosis relies on electrocardiogram (ECG) and troponin tests, but troponin tests are accurate only after 12-24 hours. Therefore, we propose much earlier detection method combining phonocardio...

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Bibliographic Details
Main Authors: Ira Puspasari, Nur Ahmadi, Miftah Pramudyo, Nobuo Watanabe, Tati L. R. Mengko, Agung W. Setiawan, Trio Adiono
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Myocardial infarction
phonocardiogram
mutual information
feature selection
machine learning
Online Access:https://ieeexplore.ieee.org/document/10741566/

Internet

https://ieeexplore.ieee.org/document/10741566/

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