Matthieu-P Schapranow, Mozhgan Bayat, Aadil Rasheed, Marcel Naik, Verena Graf, Danilo Schmidt, Klemens Budde, Héloïse Cardinal, Ruth Sapir-Pichhadze, Franz Fenninger, Karen Sherwood, Paul Keown, Oliver P Günther, Konstantin D Pandl, Florian Leiser, Scott Thiebes, Ali Sunyaev, Matthias Niemann, Andreas Schimanski, Thomas Klein
BACKGROUND: Recent advances in hardware and software enabled the use of artificial intelligence (AI) algorithms for analysis of complex data in a wide range of daily-life use cases. We aim to explore the benefits of applying AI to a specific use case in transplant nephrology: risk prediction for severe posttransplant events. For the first time, we combine multinational real-world transplant data, which require specific legal and technical protection measures. OBJECTIVE: The German-Canadian NephroCAGE consortium aims to develop and evaluate specific processes, software tools, and methods to (1) combine transplant data of more than 8000 cases over the past decades from leading transplant centers in Germany and Canada, (2) implement specific measures to protect sensitive transplant data, and (3) use multinational data as a foundation for developing high-quality prognostic AI models...
December 22, 2023: JMIR Research Protocols