Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

• Glavni autori: Sergiu Carpov (Autor), Nicolas Gama (Autor), Mariya Georgieva (Autor), Juan Ramon Troncoso-Pastoriza (Autor)
• Format: Knjiga
• Izdano: BMC, 2020-07-01T00:00:00Z.
• Teme: article
• Online pristup: Connect to this object online.

Abstract Background Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the global population. It enables medical research algorithms to be securely deployed in the cl...