The German-Canadian consortium NephroCAGE is cooperating to demonstrate the added value of artificial intelligence (AI) using the concrete clinical example of kidney transplantation. Inadequate kidney function requires regular dialysis: there are currently around 100,000 dialysis patients in Germany, and around half that number in Canada. Dialysis costs approximately 30-40k EUR per patient per year. In comparison, a kidney transplant costs around 15-20 thousand euros. In 2019, more than 2,100 kidney transplants were performed in Germany (German Organ Transplant Foundation) and more than 1,700 in Canada (Canadian Institute for Health in Canada). However, suitable donor organs are rare: in Germany, for example, there are more than 7,000 patients on a waiting list, and in Canada more than 3,000. Even after a transplant, there is a risk of complications that can lead to severe limitations in kidney function or, in the worst case, even total loss of the organ.

The consortium partners are creating a learning AI system to match organ donors and recipients even more precisely in advance (matching) and thus prevent risks in kidney transplants. To this end, clinical centers of excellence in both nations are contributing transplant data from the last ten years. They will be analyzed using AI learning techniques and combined together with a novel matching algorithm to create clinical prognostic models for kidney transplant patients. By using a federated learning approach, where the algorithms are executed at the location of the data, data protection is maintained and sensitive health data from both nations can serve as a common basis for clinical prognostic models for the first time. As a result, a clinical demonstrator will be created to serve the exploitation of the medical and technical innovations in the context of care, as well as a basis for exploitation and follow-on projects.