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Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity.

Privacy preserving data mining for medical information is an important issue to guarantee confidentiality of integrated multiple data sets. In this paper, we propose a secured scheme to estimate related risk of cancers accurately and effectively in a privacy-preserving way. We study models to config...

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Published in:Journal of Medical Systems Vol. 42; no. 5; pp. 1 - 2
Main Authors: Kikuchi, Hiroaki, Huang, Xuping, Ikuji, Shigeta, Inoue, Manami
Format: algorithm equations & formulas research tables/charts Journal Article
Published: Springer Nature May2018
Online Access:View this record in EBSCOhost
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      dt: May2018
      vid: 42
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-018-0930-9
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        atl: Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity.
      aug:
        au:
          Kikuchi, Hiroaki
          Huang, Xuping
          Ikuji, Shigeta
          Inoue, Manami
        affil: School of Interdisciplinary Mathematical Sciences, Meiji University, 4-21-1 Nakano, 164-8525, Tokyo, Japan
      sug:
        subj:
          Data Mining
          Privacy and Confidentiality
          Neoplasms Risk Factors
          Physical Activity
          Human
          Radiation Dosage
          Smoking
          Chi Square Test
          Patient Identification
          Algorithms
          Intellectual Property
          Data Analytics
          Epidemiology
          Japan
      ab: Privacy preserving data mining for medical information is an important issue to guarantee confidentiality of integrated multiple data sets. In this paper, we propose a secured scheme to estimate related risk of cancers accurately and effectively in a privacy-preserving way. We study models to configure the appropriate set of attributes to reduce risk of identity of an individual from being determined. We examine the proposed privacy preserving protocol for encrypted hypothesis test, using actual cohort data supplied by National Cancer Center.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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