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Author

Masahiro Ohwada

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Open access Jul 2026

Improved accuracy of PCG signal classification for myocardial infarction biomarker using automatic feature selection and boosting process

Myocardial infarction (MI) is a leading global health concern, typically diagnosed using ECG, biomarkers, or imaging, which costly or unavailable in low-resource settings. This study presents a non-invasive, machine learning-based approach using phonocardiogram (PCG) signals for classifying normal, ST-elevation MI (S...

Ira Puspasari, Nobuo Watanabe, Masahiro Ohwada et al. · 0 citations

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