Published on in Vol 6, No 2 (2018): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9455, first published .
Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources

Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources

Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources

Yingxiang Huang   1 * , BA ;   Junghye Lee   2, 3, 4 * , PhD ;   Shuang Wang   1 , PhD ;   Jimeng Sun   5 , PhD ;   Hongfang Liu   6 , PhD ;   Xiaoqian Jiang   1 , PhD

1 Health Sciences, Department of Biomedical Informatics, University of California - San Diego, La Jolla, CA, United States

2 School of Management Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

3 Department of Biomedical Informatics, University of California - San Diego, La Jolla, CA, United States

4 Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea

5 School of Computational Science and Engineering at College of Computing, Georgia Institute of Technology, Atlanta, GA, United States

6 Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, United States

*these authors contributed equally

Corresponding Author:

  • Yingxiang Huang, BA
  • Health Sciences
  • Department of Biomedical Informatics
  • University of California - San Diego
  • 9500 Gilman Dr
  • La Jolla, CA, 92093
  • United States
  • Phone: 1 858 534 2230
  • Email: yih108@eng.ucsd.edu