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

Cardiac Disease Management (80) Clinical Information and Decision Making (1328) Cardiology (130) Decision Support for Health Professionals (1136) Machine Learning (1383) Artificial Intelligence (1194)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45352, first published .
Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches

Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches

Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches

Authors of this article:

Michael O Killian1 Author Orcid Image ;   Shubo Tian2 Author Orcid Image ;   Aiwen Xing2 Author Orcid Image ;   Dana Hughes1 Author Orcid Image ;   Dipankar Gupta3 Author Orcid Image ;   Xiaoyu Wang2 Author Orcid Image ;   Zhe He4 Author Orcid Image
Article Authors Cited by (1) Tweetations (9) Metrics

Michael O Killian   1 * , MSW, PhD ;   Shubo Tian   2 * , PhD ;   Aiwen Xing   2 , MSc, PhD ;   Dana Hughes   1 , BSc ;   Dipankar Gupta   3 , MD ;   Xiaoyu Wang   2 , BSc, MSc ;   Zhe He   4 * , MSc, PhD

1 College of Social Work, Florida State University, Tallahassee, FL, United States

2 Department of Statistics, Florida State University, Tallahassee, FL, United States

3 Congenital Heart Center, Shands Children’s Hospital, University of Florida, Gainesville, FL, United States

4 School of Information, Florida State University, Tallahassee, FL, United States

*these authors contributed equally

Corresponding Author:

  • Zhe He, MSc, PhD
  • School of Information
  • Florida State University
  • 142 Collegiate Loop
  • Tallahassee, FL, 32306
  • United States
  • Phone: 1 850 644 5775
  • Email: zhe@fsu.edu