Swarm learning and how AI can improve cancer diagnosis and treatment
AI is capable of analyzing large amounts of data and recognizing certain patterns. These insights can help to better predict the course of the disease or to make more individualized diagnoses. But AI tools have so far only been used hesitantly in routine clinical practice.
A key reason is that AI requires training on large and diverse multi-centric datasets. In practice, data sharing between hospitals is severely restricted by legal and ethical hurdles. A technical solution to this problem is swarm learning. It is a special form of machine learning in which models are trained without exchanging data between institutions. The coordination and merging of models are performed via a blockchain, eliminating the need for a central instance.
The DECADE project builds on this method:
Using SL-based AI technology it will solve real-world clinical problems related to colorectal cancer.