Literature DB >> 21636164

Privacy-preserving models for comparing survival curves using the logrank test.

Tingting Chen1, Sheng Zhong.   

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.
Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Mesh:

Year:  2011        PMID: 21636164     DOI: 10.1016/j.cmpb.2011.04.004

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  2 in total

1.  Preserving Institutional Privacy in Distributed binary Logistic Regression.

Authors:  Yuan Wu; Xiaoqian Jiang; Lucila Ohno-Machado
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

2.  Protecting patient privacy in survival analyses.

Authors:  Luca Bonomi; Xiaoqian Jiang; Lucila Ohno-Machado
Journal:  J Am Med Inform Assoc       Date:  2020-03-01       Impact factor: 4.497

  2 in total

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