The DZNE has established the DZNE Swarm Learning Hub, which will provide scientific expertise and the software technology for projects utilizing biomedical data across organizations, including the Cluster of Excellence ImmunoSensation.

The Swarm Learning Hub comprises a section for decentralized data management (including data standardization following FAIR principles) as well as a section for Swarm Learning adaptation of AI/ML algorithms (sandbox function), will provide consultation on aspects such as cybersecurity, and will advise on legal and organizational aspects concerning the development of Swarm Learning networks. The Swarm Learning Hub will serve as a community platform for exchanging information concerning decentralized AI/ML applications.

The Swarm Learning Hub’s mission is to contribute to a cultural change, namely from data sharing to data visiting principles, which will allow us to collaborate with colleagues in countries, organizations and institutions that cannot share their data due to diverse reasons (e.g., data privacy, legal, organizational, data size).

These principles will substantially facilitate the large, collaborative international efforts necessary to identify and validate biomarkers in real-world applications for patient stratification and diagnostics, risk prediction, and the selection of precise treatments.

You can find more information here: dzne.de/swarm-learning-hub

Steering Committee

Dr. Anna Aschenbrenner

Dr. Matthias Becker

Dr. Lorenzo Bonaguro

Dr. Tal Pecht

Prof. Dr. Joachim L. Schultze

Dr. Thomas Ulas

Publications

  • Schultze JL. Building Trust in Medical Use of Artificial Intelligence – The Swarm Learning Principle. Journal of CME (2023), 12(1). DOI: 10.1080/28338073.2022.2162202
  • Schultze JL, Büttner M & Becker M. Swarm immunology: harnessing blockchain technology and artificial intelligence in human immunology. Nat Rev Immunol 22, 401–403 (2022). DOI: 10.1038/s41577-022-00740-1
  • Becker M. Swarm learning for decentralized healthcare. Hautarzt 73, 323–325 (2022). DOI: 10.1007/s00105-021-04940-z
  • Warnat-Herresthal S, Schultze H, Shastry KL […], Aschenbrenner AC, […], Ulas T, […], Becker M, […], Schultze JL. Swarm Learning for decentralized and confidential clinical machine learning. Nature 594, 265–270 (2021). DOI: 10.1038/s41586-021-03583-3