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

被引:5
|
作者
Chen, Tingting [1 ]
Zhong, Sheng [1 ]
机构
[1] SUNY Buffalo, Dept Comp Sci & Engn, Amherst, NY 14260 USA
关键词
Survival curves; Privacy preservation; Logrank test;
D O I
10.1016/j.cmpb.2011.04.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:249 / 253
页数:5
相关论文
共 50 条
  • [1] COMPARISON OF SURVIVAL CURVES - LOGRANK TEST
    RODARY, C
    LAPLANCHE, A
    NOUGUE, CC
    FLAMANT, R
    BULLETIN DU CANCER, 1981, 68 (02) : 201 - 204
  • [2] Scorpio: A Simple, Convenient, Microsoft Excel Macro Based Program for Privacy-Preserving Logrank Test
    Li, Yu
    Zhong, Sheng
    COMPUTER APPLICATIONS FOR DATABASE, EDUCATION, AND UBIQUITOUS COMPUTING, 2012, 352 : 86 - 91
  • [3] Privacy-preserving distributed clustering using generative models
    Merugu, S
    Ghosh, J
    THIRD IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS, 2003, : 211 - 218
  • [4] Privacy-preserving encryption scheme using DNA parentage test
    Gritti, Clementine
    Susilo, Willy
    Plantard, Thomas
    Khin Than Win
    THEORETICAL COMPUTER SCIENCE, 2015, 580 : 1 - 13
  • [5] Privacy-preserving Kruskal-Wallis test
    Guo, Suxin
    Zhong, Sheng
    Zhang, Aidong
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2013, 112 (01) : 135 - 145
  • [6] Privacy-preserving Deep-learning Models for Fingerprint Data Using Differential Privacy
    Mohammadi, Maryam
    Sabry, Farida
    Labda, Wadha
    Malluhi, Qutaibah
    PROCEEDINGS OF THE 9TH ACM INTERNATIONAL WORKSHOP ON SECURITY AND PRIVACY ANALYTICS, IWSPA 2023, 2023, : 45 - 53
  • [7] Investigation of Privacy-Preserving Data Models and Contributions
    Ahuja, Kamlesh
    Sharma, Navneet
    Mishra, Durgesh Kumar
    Vyas, Ram Krishan
    PROCEEDINGS OF THE 2019 6TH INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2019, : 779 - 783
  • [8] Truthful and privacy-preserving generalized linear models
    Qiu, Yuan
    Liu, Jinyan
    Wang, Di
    INFORMATION AND COMPUTATION, 2024, 301
  • [9] Privacy-Preserving Speaker Verification and Identification Using Gaussian Mixture Models
    Pathak, Manas A.
    Raj, Bhiksha
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2013, 21 (02): : 397 - 406
  • [10] PRIVACY-PRESERVING AUTHENTICATION USING FINGERPRINT
    Feng, Quan
    Su, Fei
    Cai, Anni
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2012, 8 (11): : 8001 - 8018