• DocumentCode
    3200737
  • Title

    On privacy-preserving publishing of spontaneous ADE reporting data

  • Author

    Wen-Yang Lin ; Duan-Chun Yang

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
  • fYear
    2013
  • fDate
    18-21 Dec. 2013
  • Firstpage
    51
  • Lastpage
    53
  • Abstract
    In this paper, we present the problem of and research issues for anonymizing spontaneous ADE reporting data for privacy-preserving ADR signal detection. Three main characteristics of spontaneous ADE data are identified, including rare ADE events, multiple individual records, and no sensitive attribute but having quasi-sensitive attributes. We examine the feasibility of contemporary privacy-preserving models for anonymizing SRS datasets, showing their incompetence in handling the these issues and so arouse the need of new privacy models and data anonymizing methods.
  • Keywords
    data privacy; drugs; medical information systems; SRS datasets; data anonymizing methods; multiple individual records; privacy-preserving ADR signal detection; privacy-preserving publishing; quasi-sensitive attributes; rare ADE events; spontaneous ADE reporting data; Data models; Data privacy; Diseases; Drugs; Privacy; Publishing; Vaccines; ADR detection; adverse drug event; privacy-preserving data publishing; spontaneous reporting system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
  • Conference_Location
    Shanghai
  • Type

    conf

  • DOI
    10.1109/BIBM.2013.6732760
  • Filename
    6732760