@article{285cddae5512420d841af5af819fe24b,
title = "Federated machine learning in data-protection-compliant research",
author = "Alissa Brauneck and Louisa Schmalhorst and \{Kazemi Majdabadi\}, \{Mohammad Mahdi\} and Mohammad Bakhtiari and Uwe V{\"o}lker and Saak, \{Christina Caroline\} and Jan Baumbach and Linda Baumbach and Gabriele Buchholtz",
note = "Funding Information: Our work was funded by the German Federal Ministry of Education and Research (BMBF; grants 16DTM100A and 16DTM100C). We also received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement no. 826078. This publication reflects only the authors{\textquoteright} views, and the European Commission is not responsible for any use that may be made of the information it contains. Funding Information: Our work was funded by the German Federal Ministry of Education and Research (BMBF; grants 16DTM100A and 16DTM100C). We also received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement no. 826078. This publication reflects only the authors{\textquoteright} views, and the European Commission is not responsible for any use that may be made of the information it contains. ",
year = "2023",
month = jan,
doi = "10.1038/s42256-022-00601-5",
language = "English",
volume = "5",
pages = "2--4",
journal = "Nature Machine Intelligence",
issn = "2522-5839",
publisher = "Springer International Publishing",
number = "1",
}