Collaborative privacy-preserving analysis of oncological data using multiparty homomorphic encryption.

ABSTRACT: Real-world healthcare data sharing is instrumental in constructing broader-based and larger clinical datasets that may improve clinical decision-making research and outcomes. Stakeholders are frequently reluctant to share their data without guaranteed patient privacy, proper protection of their datasets, and control over the usage of their data. Fully homomorphic encryption (FHE) is a cryptographic capability that can address these issues by enabling computation on encrypted data without intermediate decryptions, so the analytics results are obtained without revealing the raw data. This work presents a toolset for collaborative privacy-preserving analysis of oncological data using multiparty FHE. Our toolset supports survival analysis, logistic regression training, and several common descr

SUBMITTER: Geva R 

PROVIDER: S-EPMC10437415 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature