Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42621, first published .

Journals

  1. Hartebrodt A, Röttger R, Blumenthal D. Federated singular value decomposition for high-dimensional data. Data Mining and Knowledge Discovery 2024;38(3):938 View
  2. Späth J, Sewald Z, Probul N, Berland M, Almeida M, Pons N, Le Chatelier E, Ginès P, Solé C, Juanola A, Pauling J, Baumbach J. Privacy-Preserving Federated Survival Support Vector Machines for Cross-Institutional Time-To-Event Analysis: Algorithm Development and Validation. JMIR AI 2024;3:e47652 View
  3. Pirmani A, Oldenhof M, Peeters L, De Brouwer E, Moreau Y. Accessible Ecosystem for Clinical Research (Federated Learning for Everyone): Development and Usability Study. JMIR Formative Research 2024;8:e55496 View
  4. Tajabadi M, Martin R, Heider D. Privacy-Preserving Decentralized Learning Methods for Biomedical Applications. Computational and Structural Biotechnology Journal 2024 View
  5. Hausleitner C, Mueller H, Holzinger A, Pfeifer B. Collaborative weighting in federated graph neural networks for disease classification with the human-in-the-loop. Scientific Reports 2024;14(1) View