Decouple and Decorrelate: A Disentanglement Security Framework Combining Sample Weighting for Cross-Institution Biased Disease Diagnosis-Reference-Cited by-同舟云学术

Decouple and Decorrelate: A Disentanglement Security Framework Combining Sample Weighting for Cross-Institution Biased Disease Diagnosis

Author:

Zhang Jiayu¹^ORCID,Li Hang²,Xu Dexuan¹^ORCID,Lou Yiwei³,Ran Menglong²,Jin Zhi³^ORCID,Huang Yu⁴^ORCID

Affiliation:

1. School of Software and Microelectronics, Peking University, Beijing, China

2. Department of Dermatology, Peking University First Hospital, Beijing, China

3. Key Laboratory of High Confidence Software Technologies, Ministry of Education, School of Computer Science, Peking University, Beijing, China

4. National Engineering Research Center for Software Engineering, Peking University, Beijing, China

Funder

National Key Research and Development Program of China

Beijing Nova Program and Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

Reference55 articles.

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. Liver Fibrosis Classification based on Multimodal Imaging Feature Fusion;2024 IEEE 11th International Conference on Cyber Security and Cloud Computing (CSCloud);2024-06-28