End-to-end privacy preserving deep learning on multi-institutional medical imaging
Georgios Kaissis, Alexander Ziller, Jonathan Passerat‐Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Da Lima, Jason Mancuso, Friederike Jungmann, M. Steinborn, Andreas Saleh, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren
Topics & Concepts
Computer scienceUSableInferenceConvolutional neural networkEncryptionDeep learningArtificial intelligenceMachine learningInformation privacyEnd-to-end principleComputer securityData miningWorld Wide WebPrivacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and EducationCOVID-19 diagnosis using AI