The FeatureCloud Platform for Federated Learning in Biomedicine: Unified Approach

• Egile Nagusiak: Julian Matschinske (Egilea), Julian Späth (Egilea), Mohammad Bakhtiari (Egilea), Niklas Probul (Egilea), Mohammad Mahdi Kazemi Majdabadi (Egilea), Reza Nasirigerdeh (Egilea), Reihaneh Torkzadehmahani (Egilea), Anne Hartebrodt (Egilea), Balazs-Attila Orban (Egilea), Sándor-József Fejér (Egilea), Olga Zolotareva (Egilea), Supratim Das (Egilea), Linda Baumbach (Egilea), Josch K Pauling (Egilea), Olivera Tomašević (Egilea), Béla Bihari (Egilea), Marcus Bloice (Egilea), Nina C Donner (Egilea), Walid Fdhila (Egilea), Tobias Frisch (Egilea), Anne-Christin Hauschild (Egilea), Dominik Heider (Egilea), Andreas Holzinger (Egilea), Walter Hötzendorfer (Egilea), Jan Hospes (Egilea), Tim Kacprowski (Egilea), Markus Kastelitz (Egilea), Markus List (Egilea), Rudolf Mayer (Egilea), Mónika Moga (Egilea), Heimo Müller (Egilea), Anastasia Pustozerova (Egilea), Richard Röttger (Egilea), Christina C Saak (Egilea), Anna Saranti (Egilea), Harald H H W Schmidt (Egilea), Christof Tschohl (Egilea), Nina K Wenke (Egilea), Jan Baumbach (Egilea)
• Formatua: Liburua
• Argitaratua: JMIR Publications, 2023-07-01T00:00:00Z.
• Gaiak: article
• Sarrera elektronikoa: Connect to this object online.

BackgroundMachine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federa...