5 citations · 12 across the 6 of their papers we have counts for
3 papers · 1 filter
Bringing the Algorithms to the Data -- Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC)
Marius de Arruda Botelho Herr, Michael Graf, Peter Placzek +11
The need for data privacy and security -- enforced through increasingly strict data protection regulations -- renders the use of healthcare data for machine learning difficult. In…
COmic: Convolutional Kernel Networks for Interpretable End-to-End Learning on (Multi-)Omics Data
Jonas C. Ditz, Bernhard Reuter, Nico Pfeifer
Motivation: The size of available omics datasets is steadily increasing with technological advancement in recent years. While this increase in sample size can be used to improve th…
CECILIA: Comprehensive Secure Machine Learning Framework
Ali Burak Ünal, Nico Pfeifer, Mete Akgün
Since ML algorithms have proven their success in many different applications, there is also a big interest in privacy preserving (PP) ML methods for building models on sensitive da…