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基于迁移学习的心肺音诊断算法

Cross-Domain Transfer Learning for PCG Diagnosis Algorithm.

机构信息

School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.

School of Journalism and Communication, Xiamen University, Xiamen 361005, China.

出版信息

Biosensors (Basel). 2021 Apr 20;11(4):127. doi: 10.3390/bios11040127.

Abstract

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.

摘要

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。

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