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
Link To Document