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Volume 11 Supplement 4

Proceedings of the 6th iDASH Privacy and Security Workshop 2017

Proceedings

Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.

Orlando, FL, USA14 October 2017

Workshop website

Edited by Shuang Wang, Xiaoqian Jiang, XiaoFeng Wang and Haixu Tang.

  2. One of the tasks in the 2017 iDASH secure genome analysis competition was to enable training of logistic regression models over encrypted genomic data. More precisely, given a list of approximately 1500 patien...

    Authors: Hao Chen, Ran Gilad-Bachrach, Kyoohyung Han, Zhicong Huang, Amir Jalali, Kim Laine and Kristin Lauter
    Citation: BMC Medical Genomics 2018 11(Suppl 4):81
    Content type: Research Published on:

  3. Logistic regression is a popular technique used in machine learning to construct classification models. Since the construction of such models is based on computing with large datasets, it is an appealing idea ...

    Authors: Charlotte Bonte and Frederik Vercauteren
    Citation: BMC Medical Genomics 2018 11(Suppl 4):86
    Content type: Research Published on:

  4. Security concerns have been raised since big data became a prominent tool in data analysis. For instance, many machine learning algorithms aim to generate prediction models using training data which contain se...

    Authors: Andrey Kim, Yongsoo Song, Miran Kim, Keewoo Lee and Jung Hee Cheon
    Citation: BMC Medical Genomics 2018 11(Suppl 4):83
    Content type: Research Published on:
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Annual Journal Metrics

  • Citation Impact
    3.622 - 2-year Impact Factor (2021)
    3.554 - 5-year Impact Factor (2021)
    0.879 - SNIP (Source Normalized Impact per Paper)
    0.955 - SJR (SCImago Journal Rank)

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BMC Medical Genomics

ISSN: 1755-8794

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