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.
[1]
C. Redhead.
The Health Information Technology for Economic and Clinical Health (HITECH) Act
,
2009
.
[2]
Whose scans are they, anyway?
,
2000,
Nature.
[3]
Douglas G. Altman,et al.
Practical statistics for medical research
,
1990
.
[4]
Glenn Fung,et al.
Privacy-preserving cox regression for survival analysis
,
2008,
KDD.
[5]
Chris Clifton,et al.
Privacy-preserving distributed mining of association rules on horizontally partitioned data
,
2004,
IEEE Transactions on Knowledge and Data Engineering.