Medical Use Case
Thousands of patients are suffering from kidney insufficiency requiring regular dialysis. These patients have to wait years for a matching donor organ due to the limited availability. However, even after a successful transplantation the risk of graft rejection or failure are unpredictable. NephroCAGE combines multi-dimensional data from historic transplant cases with latest artificial intelligence algorithms to explore new risk factors for severe clinical endpoints after transplantation.
The combination of clinical data, lab data, and genetic data requires adequate tools. NephroCAGE develops a federated infrastructure for machine learning, which enables secure and reproducible exchange of clinical prediction models between partners.
The combination of Canadian and German expertise helps to cover specifics from all over the world making clinical prediction models more reliable. NephroCAGE combines latest artificial intelligence algorithms with modern transfer learning techniques improving the quality of model predictions.
Read the latest news from the NephroCAGE team here.
Stay tuned to learn more about AI in nephrology, we keep you posted.