| Autor: |
Tseng, Kuo-Kun, Wang, Chao, Huang, Yu-Feng, Chen, Guan-Rong, Yung, Kai-Leung, Ip, Wai-Hung |
| Předmět: |
|
| Zdroj: |
Biosensors (2079-6374); Apr2021, Vol. 11 Issue 4, p127-127, 1p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
