School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.
School of Journalism and Communication, Xiamen University, Xiamen 361005, China.
Biosensors (Basel). 2021 Apr 20;11(4):127. doi: 10.3390/bios11040127.
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.
Cardiechema 是一种反映心血管疾病的方法,医生使用听诊器通过声音图谱来帮助确定心脏状况。本文使用心音图(PCG)作为诊断信号,并提出了一种深度学习诊断框架。通过改进架构和模块,主要采用了新的迁移学习和提升架构。此外,还设计了一种分割方法来改进现有的信号分割方法,例如 R 波到 R 波间隔分割和固定分割。在评估方面,最终的诊断架构在公共的 PCG 数据库上实现了可持续的性能。