3.1k citations · 3.1k across the 5 of their papers we have counts for
5 papers
Industry-Scale Orchestrated Federated Learning for Drug Discovery
Martijn Oldenhof, Gergely Ács, Balázs Pejó +44
To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n°831472), whic…
Collaborative Drug Discovery: Inference-level Data Protection Perspective
Balazs Pejo, Mina Remeli, Adam Arany +2
Pharmaceutical industry can better leverage its data assets to virtualize drug discovery through a collaborative machine learning platform. On the other hand, there are non-negligi…
The Future of Digital Health with Federated Learning
Nicola Rieke, Jonny Hancox, Wenqi Li +14
Data-driven Machine Learning has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern…
Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning
Mathieu N Galtier, Camille Marini
Machine learning is promising, but it often needs to process vast amounts of sensitive data which raises concerns about privacy. In this white-paper, we introduce Substra, a distri…
Morpheo: Traceable Machine Learning on Hidden data
Mathieu Galtier, Camille Marini
Morpheo is a transparent and secure machine learning platform collecting and analysing large datasets. It aims at building state-of-the art prediction models in various fields wher…