| Autor: |
Kuo-Kun Tseng, Chao Wang, Yu-Feng Huang, Guan-Rong Chen, Kai-Leung Yung, Wai-Hung Ip |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Biosensors, Vol 11, Iss 4, p 127 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2079-6374 |
| DOI: |
10.3390/bios11040127 |
| Popis: |
Cardiechema is a way to reflect cardiovascular disease where the doctor uses a stethoscope to help determine the heart condition with a sound map. In this paper, phonocardiogram (PCG) is used as a diagnostic signal, and a deep learning diagnostic framework is proposed. By improving the architecture and modules, a new transfer learning and boosting architecture is mainly employed. In addition, a segmentation method is designed to improve on the existing signal segmentation methods, such as R wave to R wave interval segmentation and fixed segmentation. For the evaluation, the final diagnostic architecture achieved a sustainable performance with a public PCG database. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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