Using the Teachable Machine Online Platform to Diagnose Cardiovascular Diseases
https://doi.org/10.25205/1818-7900-2025-23-3-57-66
Abstract
The possibility of improving the quality of cardiovascular disease diagnostics by using machine learning is presented. The article discusses digital equipment for obtaining audiograms. A data set for machine learning of a cardiovascular disease classification model is described. One of the sections is devoted to the development of a web application for remote diagnostics using the obtained model.
About the Authors
D. M. Popov
Kemerovo State Medical University
Russian Federation
Russian Federation
Dmitry M. Popov, Candidate of Technical Sciences, Associate Professor
Kemerovo
E. V. Prosvirkina
Kemerovo State Medical University
Russian Federation
Russian Federation
Elena V. Prosvirkina, Candidate of Chemical Sciences, Head of the Department of Medical, Biological Physics and Higher Mathematics, Associate Professor
Kemerovo
A. Y. Sakharchuk
Kemerovo State Medical University
Russian Federation
Russian Federation
Alexey Yu. Sakharchuk, Resident Physician
Kemerovo
S. D. Rudnev
Kemerovo State Medical University
Russian Federation
Russian Federation
Sergey D. Rudnev, Doctor of Technical Sciences, Professor
Kemerovo
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Review
For citations:
Popov D.M., Prosvirkina E.V., Sakharchuk A.Y., Rudnev S.D. Using the Teachable Machine Online Platform to Diagnose Cardiovascular Diseases. Vestnik NSU. Series: Information Technologies. 2025;23(3):57-66. (In Russ.) https://doi.org/10.25205/1818-7900-2025-23-3-57-66
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