Federated Survival Forests
Author:
Affiliation:
1. Politecnico di Milano,DEIB,Milan,Italy
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10190990/10190992/10190999.pdf?arnumber=10190999
Reference60 articles.
1. Federated Cox Proportional Hazards Model with multicentric privacy-preserving LASSO feature selection for survival analysis from the perspective of personalized medicine
2. scikit-survival: A library for time-to-event analysis built on top of scikit-learn;polsterl;Journal of Machine Learning Research,2020
3. Accurate training of the Cox proportional hazards model on vertically-partitioned data while preserving privacy
4. DC-COX: Data collaboration Cox proportional hazards model for privacy-preserving survival analysis on multiple parties
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