| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560734 |
| ISSN: | 1405-5546 |
| Autors: | Tovar Corona, Blanca2 Flores Alonso, Santiago Isaac1 Luna García, René1 |
| Institucions: | 1Instituto Politécnico Nacional, Centro de Investigación en Computación, México 2Instituto Politécnico Nacional, Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, México |
| Any: | 2022 |
| Període: | Jul-Sep |
| Volum: | 26 |
| Número: | 3 |
| Paginació: | 1143-1150 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | Heart Valve Disease (HVD) encompasses a number of common cardiovascular conditions that account for a significant percentage of heart diseases. At present, the acoustic phenomena generated by the abnormal functioning of the heart valves can be recorded and digitized using electronic stethoscopes known as phonocardiographs. The analysis of the phonocardiographic signals has made it possible to indicate that the normal and pathological records differ in terms of both temporal and spectral characteristics. The present work describes the construction and implementation of a Deep Learning (DL) algorithm for the binary classification of normal and abnormal heart sounds. The performance of this approach reached an accuracy higher than 98 % and specificities in the ”Normal” class of up to 99 %. |
| Keyword: | Artificial intelligence, Deep neural network, Phonocardiography, Heart valve disease |
| Text complet: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
