Fed-MStacking: Heterogeneous Federated Learning With Stacking Misaligned Labels for Abnormal Heart Sound Detection-Reference-Cited by-同舟云学术

Fed-MStacking: Heterogeneous Federated Learning With Stacking Misaligned Labels for Abnormal Heart Sound Detection

Published:2024-09 Issue:9 Volume:28 Page:5055-5066
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Qiu Wanyong¹^ORCID,Feng Yifan¹^ORCID,Li Yuying¹^ORCID,Chang Yi²^ORCID,Qian Kun¹^ORCID,Hu Bin¹^ORCID,Yamamoto Yoshiharu³^ORCID,Schuller Björn W.²^ORCID

Affiliation:

1. Key Laboratory of Brain Health Intelligent Evaluation and Intervention (BIT), Ministry of Education, Beijing, China

2. GLAM – the Group on Language, Audio, & Music, Imperial College London, London, U.K.

3. Educational Physiology Laboratory, Graduate School of Education, The University of Tokyo, Tokyo, Japan

Funder

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Beijing Institute of Technology, China

Japan Society for the Promotion of Science

Ministry of Education, Culture, Sports, Science and Technology

JSPS KAKENHI

JST-Mirai Program

JST MOONSHOT Program

BIT Research and Innovation Promoting

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6221020/10666866/10599790.pdf?arnumber=10599790

Reference57 articles.

1. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019

2. A Review of Computer-Aided Heart Sound Detection Techniques

3. Heart Sound: Detection and Analytical Approach Towards Diseases

4. Advanced heart sound analysis as a new prognostic marker in stable coronary artery disease

5. Deep Wavelets for Heart Sound Classification