11 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.CR2019★ 11 cited
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…
q-bio.QM2017
Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy
Laetitia Le, Camille Marini, Alexandre Gramfort +9
Monoclonal antibodies constitute one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. In order to guar…