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

Proposals (eHealth) (86) Clinical Information and Decision Making (1914) Data Science (357) Decision Support for Health Professionals (1538) Machine Learning (2074) Artificial Intelligence (2122) Tools, Programs and Algorithms (376) Development and Evaluation of Research Methods, Instruments and Tools (743) Nephrology/Renal Disorders (99)

Published on in Vol 12 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48892, first published .
NephroCAGE—German-Canadian Consortium on AI for Improved Kidney Transplantation Outcome: Protocol for an Algorithm Development and Validation Study

NephroCAGE—German-Canadian Consortium on AI for Improved Kidney Transplantation Outcome: Protocol for an Algorithm Development and Validation Study

NephroCAGE—German-Canadian Consortium on AI for Improved Kidney Transplantation Outcome: Protocol for an Algorithm Development and Validation Study

Authors of this article:

Matthieu-P Schapranow1 Author Orcid Image ;   Mozhgan Bayat1 Author Orcid Image ;   Aadil Rasheed1 Author Orcid Image ;   Marcel Naik2 Author Orcid Image ;   Verena Graf3 Author Orcid Image ;   Danilo Schmidt3 Author Orcid Image ;   Klemens Budde2 Author Orcid Image ;   Héloïse Cardinal4 Author Orcid Image ;   Ruth Sapir-Pichhadze5 Author Orcid Image ;   Franz Fenninger6 Author Orcid Image ;   Karen Sherwood6 Author Orcid Image ;   Paul Keown6 Author Orcid Image ;   Oliver P Günther7 Author Orcid Image ;   Konstantin D Pandl8 Author Orcid Image ;   Florian Leiser8 Author Orcid Image ;   Scott Thiebes8 Author Orcid Image ;   Ali Sunyaev8 Author Orcid Image ;   Matthias Niemann9 Author Orcid Image ;   Andreas Schimanski9 Author Orcid Image ;   Thomas Klein10 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Journals

  1. Aksoy G, Akçay H, Arı Ç, Adar M, Koyun M, Çomak E, Akman S. Predicting graft survival in paediatric kidney transplant recipients using machine learning. Pediatric Nephrology 2025;40(1):203 View
  2. Olawade D, Marinze S, Qureshi N, Weerasinghe K, Teke J. The impact of artificial intelligence and machine learning in organ retrieval and transplantation: A comprehensive review. Current Research in Translational Medicine 2025;73(2):103493 View
  3. Salybekov A, Yerkos A, Sedlmayr M, Wolfien M. Ethics and Algorithms to Navigate AI’s Emerging Role in Organ Transplantation. Journal of Clinical Medicine 2025;14(8):2775 View
  4. Wang Y, Cheungpasitporn W, Ali H, Qing J, Thongprayoon C, Kaewput W, Soliman K, Huang Z, Yang M, Zhang Z. A practical guide for nephrologist peer reviewers: evaluating artificial intelligence and machine learning research in nephrology. Renal Failure 2025;47(1) View
  5. Hohenstein B, Binder T, Kramann R. KI-Anwendungen in der nephrologischen Diagnostik. DMW - Deutsche Medizinische Wochenschrift 2025;150(23):1403 View