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

Blockchain, Distributed Ledger Apps for Health and Medicine (85) Clinical Information and Decision Making (1407) Clinical Informatics (1022) Artificial Intelligence (1371) Ethics, Privacy, and Legal Issues (479) Theoretical Frameworks and Concepts (252) New Methods (944) Machine Learning (1465) Tools, Programs and Algorithms (266)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46547, first published .
Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

Authors of this article:

Xueping Liang1 Author Orcid Image ;   Juan Zhao2 Author Orcid Image ;   Yan Chen1 Author Orcid Image ;   Eranga Bandara3 Author Orcid Image ;   Sachin Shetty3 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Xueping Liang   1 , PhD ;   Juan Zhao   2 , PhD ;   Yan Chen   1 , PhD ;   Eranga Bandara   3 , BSc, MSc ;   Sachin Shetty   3 , PhD

1 Department of Information Systems and Business Analytics, Florida International University, Miami, FL, United States

2 American Heart Association, Dallas, TX, United States

3 Virginia Modeling, Analysis and Simulation Center, Old Dominion University, Suffolk, VA, United States

Corresponding Author:

  • Xueping Liang, PhD
  • Department of Information Systems and Business Analytics
  • Florida International University
  • 11200 SW 8th St
  • Miami, FL, 33199
  • United States
  • Phone: 1 305 348 2830
  • Email: xuliang@fiu.edu