This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2226) Ethics, Privacy, and Legal Issues (458) Machine Learning (1400)

Published on in Vol 4, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17265, first published .
Stochastic Channel-Based Federated Learning With Neural Network Pruning for Medical Data Privacy Preservation: Model Development and Experimental Validation

Stochastic Channel-Based Federated Learning With Neural Network Pruning for Medical Data Privacy Preservation: Model Development and Experimental Validation

Stochastic Channel-Based Federated Learning With Neural Network Pruning for Medical Data Privacy Preservation: Model Development and Experimental Validation

Authors of this article:

Rulin Shao1 Author Orcid Image ;   Hongyu He2 Author Orcid Image ;   Ziwei Chen3 Author Orcid Image ;   Hui Liu4 Author Orcid Image ;   Dianbo Liu5 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

Rulin Shao   1 , BA ;   Hongyu He   2 , BA ;   Ziwei Chen   3 , PhD ;   Hui Liu   4 , BA ;   Dianbo Liu   5 , PhD

1 Department of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China

2 Department of Electrical Engineering, Xi'an Jiaotong University, Xi'an, China

3 Beijing Jiaotong University, Beijing, China

4 Department of Mathematics, Mianyang Vocational College, Mianyang, China

5 Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, United States

Corresponding Author:

  • Dianbo Liu, PhD
  • Computer Science and Artificial Intelligence Laboratory (CSAIL)
  • Massachusetts Institute of Technology
  • 77 Massachusetts Ave
  • Cambridge, MA, 02139
  • United States
  • Phone: 1 6177101859
  • Email: dianbo@mit.edu