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

Machine Learning (1194) Electronic Health Records (869) Adoption and Change Management of eHealth Systems (583) Tools, Programs and Algorithms (208) Ontologies, Classifications, and Coding (178) Ethics, Privacy, and Legal Issues (411)

Published on in Vol 9, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26598, first published .
Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study

Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study

Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study

Authors of this article:

Dongchul Cha 1, 2 Author Orcid Image ;   MinDong Sung 1 Author Orcid Image ;   Yu-Rang Park 1 Author Orcid Image
Article Authors Cited by (9) Tweetations (2) Metrics

Journals

  1. Chen Z, Li D, Zhu J, Zhang S. DACFL: Dynamic Average Consensus-Based Federated Learning in Decentralized Sensors Network. Sensors 2022;22(9):3317 View
  2. Prayitno , Shyu C, Putra K, Chen H, Tsai Y, Hossain K, Jiang W, Shae Z. A Systematic Review of Federated Learning in the Healthcare Area: From the Perspective of Data Properties and Applications. Applied Sciences 2021;11(23):11191 View
  3. Joshi M, Pal A, Sankarasubbu M. Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges. ACM Transactions on Computing for Healthcare 2022;3(4):1 View
  4. Rani S, Kataria A, Kumar S, Tiwari P. Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review. Knowledge-Based Systems 2023;274:110658 View
  5. Li S, Liu P, Nascimento G, Wang X, Leite F, Chakraborty B, Hong C, Ning Y, Xie F, Teo Z, Ting D, Haddadi H, Ong M, Peres M, Liu N. Federated and distributed learning applications for electronic health records and structured medical data: a scoping review. Journal of the American Medical Informatics Association 2023;30(12):2041 View
  6. Guzzo A, Fortino G, Greco G, Maggiolini M. Data and model aggregation for radiomics applications: Emerging trend and open challenges. Information Fusion 2023;100:101923 View
  7. Sharma S, Guleria K. A comprehensive review on federated learning based models for healthcare applications. Artificial Intelligence in Medicine 2023;146:102691 View

Books/Policy Documents

  1. Stripelis D, Ambite J. Artificial Intelligence for Personalized Medicine. View