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

Research Methodology - AI (34) Artificial Intelligence (2070) Chronic Conditions (424) Natural Language Processing (897)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/74066, first published .
Examining Transparency in Kidney Transplant Recipient Selection Criteria: Nationwide Cross-Sectional Study

Examining Transparency in Kidney Transplant Recipient Selection Criteria: Nationwide Cross-Sectional Study

Examining Transparency in Kidney Transplant Recipient Selection Criteria: Nationwide Cross-Sectional Study

Authors of this article:

Belen Rivera1 Author Orcid Image ;   Stalin Canizares1 Author Orcid Image ;   Gabriel Cojuc-Konigsberg1 Author Orcid Image ;   Olena Holub2 Author Orcid Image ;   Alex Nakonechnyi2 Author Orcid Image ;   Ritah R Chumdermpadetsuk1 Author Orcid Image ;   Keren Ladin3 Author Orcid Image ;   Devin E Eckhoff1 Author Orcid Image ;   Rebecca Allen2 Author Orcid Image ;   Aditya Pawar1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Belen Rivera   1 , MD ;   Stalin Canizares   1 , MD ;   Gabriel Cojuc-Konigsberg   1 , MD ;   Olena Holub   2 , BS ;   Alex Nakonechnyi   2 , PhD ;   Ritah R Chumdermpadetsuk   1 , MD ;   Keren Ladin   3 , MSc, PhD ;   Devin E Eckhoff   1 , MD ;   Rebecca Allen   2 , PhD ;   Aditya Pawar   1 , MD

1 Beth Israel Deaconess Medical Center, Boston, MA, United States

2 Department of Computer Science and Mathematics, Mount St Joseph University, Cincinnati, OH, United States

3 Department of Community Health, Research on Aging, Ethics, and Community Health (REACH Lab), Tufts University, Boston, MA, United States

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