title: Privacy-preserving models for comparing survival curves using the logrank test.
abstract: The incorporation of electronic health care in medical institutions will benefit and thus further boost the collaborations in medical research among clinics and research institutions. However, privacy regulations and security concerns make such collaborations very restricted. In this paper, we propose privacy preserving models for survival curves comparison based on logrank test, in order to perform better survival analysis through the collaboration of multiple medical institutions and protect the data privacy. We distinguish two collaboration scenarios and for each scenario we present a privacy preserving model for logrank test. We conduct experiments on the real medical data to evaluate the effectiveness of our proposed models.
authors.affiliation: Computer Science and Engineering Department, State University of New York at Buffalo, Amherst, NY 14260, USA.
authors.forename: Tingting
authors.initials: T
authors.lastname: Chen
authors.forename: Sheng
authors.initials: S
authors.lastname: Zhong
mesh_terms: D006801:Humans; D016347:Medical Records Systems, Computerized; D008962:Models, Theoretical; D016019:Survival Analysis