Privacy-preserving medical reports publishing for cluster analysis
Source of Publication
2014 6th International Conference on New Technologies, Mobility and Security - Proceedings of NTMS 2014 Conference and Workshops
Health data mining is an emerging research direction. High-quality health data mining results rely on having access to high-quality patient information. Yet, releasing patient-specific medical reports may potentially reveal sensitive information of the individual patients. In this paper, we study the problem of anonymizing medical reports and present a solution to anonymize a collection of medical reports while preserving the information utility of the medical reports for the purpose of cluster analysis. Experimental results show that our proposed approach can the impact of anonymization on the cluster quality is minor, suggesting that the feasibility of simultaneously preserving both information utility and privacy in anonymous medical reports. © 2014 IEEE.
IEEE Computer Society
Computer Sciences | Medicine and Health Sciences
anonymity, healthcare, Privacy, text clustering
Hmood, Ali; Fung, Benjamin C.M.; and Iqbal, Farkhund, "Privacy-preserving medical reports publishing for cluster analysis" (2014). All Works. 2802.
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