Machine learning analysis of heart tones from phonocardiograms enables cost-effective, non-invasive diagnosis of pulmonary hypertension suitable for primary care.
Does machine learning-based analysis of phonocardiograms diagnose pulmonary hypertension?
Machine learning-based analysis of phonocardiograms
Diagnosis of pulmonary hypertension
Machine learning-based analysis of phonocardiograms is proposed as a cost-effective, non-invasive diagnostic tool for pulmonary hypertension, particularly useful in resource-limited settings.
Absolute Event Rate: 0% vs 0%
The authors propose a way of diagnosing pulmonary hypertension through machine learning-based analysis of phonocardiograms. The technique offers a cost-effective and non-invasive solution that allows it to be used in primary healthcare. It is particularly valuable for regions with limited access to specialized clinics and highly qualified cardiologists.
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M. V. Ryabkov
V. V. Gramovich
K. V. Dmitriev
Bulletin of the Russian Academy of Sciences Physics
Lomonosov Moscow State University
National Medical Research Center of Cardiology
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Ryabkov et al. (Thu,) reported a other. Machine learning analysis of heart tones from phonocardiograms enables cost-effective, non-invasive diagnosis of pulmonary hypertension suitable for primary care.
synapsesocial.com/papers/69a286240a974eb0d3c00ea2 — DOI: https://doi.org/10.1134/s1062873825714321