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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882759/ https://www.ncbi.nlm.nih.gov/pubmed/29616341 http://dx.doi.org/10.1007/s10916-018-0930-9 |
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author | Kikuchi, Hiroaki Huang, Xuping Ikuji, Shigeta Inoue, Manami |
author_facet | Kikuchi, Hiroaki Huang, Xuping Ikuji, Shigeta Inoue, Manami |
author_sort | Kikuchi, Hiroaki |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5882759 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-58827592018-04-05 Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity Kikuchi, Hiroaki Huang, Xuping Ikuji, Shigeta Inoue, Manami J Med Syst Education & Training 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. Springer US 2018-04-04 2018 /pmc/articles/PMC5882759/ /pubmed/29616341 http://dx.doi.org/10.1007/s10916-018-0930-9 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Education & Training Kikuchi, Hiroaki Huang, Xuping Ikuji, Shigeta Inoue, Manami Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity |
title | Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity |
title_full | Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity |
title_fullStr | Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity |
title_full_unstemmed | Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity |
title_short | Privacy-Preserving Hypothesis Testing for Reduced Cancer Risk on Daily Physical Activity |
title_sort | privacy-preserving hypothesis testing for reduced cancer risk on daily physical activity |
topic | Education & Training |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882759/ https://www.ncbi.nlm.nih.gov/pubmed/29616341 http://dx.doi.org/10.1007/s10916-018-0930-9 |
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