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

Methods and Instruments in Medical Informatics (135) Ethics, Privacy, and Legal Issues (494) Innovations in Clinical Trials and Research Data Management (84) eHealth Infrastructures (357) Electronic Health Records (1068) Secondary Use of Clinical Data for Research and Surveillance (375)

Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21043, first published .
Weight-Based Framework for Predictive Modeling of Multiple Databases With Noniterative Communication Without Data Sharing: Privacy-Protecting Analytic Method for Multi-Institutional Studies

Weight-Based Framework for Predictive Modeling of Multiple Databases With Noniterative Communication Without Data Sharing: Privacy-Protecting Analytic Method for Multi-Institutional Studies

Weight-Based Framework for Predictive Modeling of Multiple Databases With Noniterative Communication Without Data Sharing: Privacy-Protecting Analytic Method for Multi-Institutional Studies

Authors of this article:

Ji Ae Park1 Author Orcid Image ;   Min Dong Sung1 Author Orcid Image ;   Ho Heon Kim1 Author Orcid Image ;   Yu Rang Park1 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Park J, Kim T, Kim J, Park Y. WICOX: Weight-Based Integrated Cox Model for Time-to-Event Data in Distributed Databases Without Data-Sharing. IEEE Journal of Biomedical and Health Informatics 2023;27(1):526 View
  2. Tarumi S, Takeuchi W, Qi R, Ning X, Ruppert L, Ban H, Robertson D, Schleyer T, Kawamoto K. Predicting pharmacotherapeutic outcomes for type 2 diabetes: An evaluation of three approaches to leveraging electronic health record data from multiple sources. Journal of Biomedical Informatics 2022;129:104001 View