Citation

Yogachandran, Rahulamathavan and Suresh, Veluru and Phan, Raphael C. -W. and Chambers, Jonathon A. and Rajarajan, Muttukrishnan (2014) Privacy-preserving clinical decision support system using Gaussian Kernel-based classification. IEEE Journal of Biomedical and Health Informatics, 18 (1). pp. 56-66. ISSN 2168-2194

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Abstract

A clinical decision support system forms a critical capability to link health observations with health knowledge to influence choices by clinicians for improved healthcare. Recent trends toward remote outsourcing can be exploited to provide efficient and accurate clinical decision support in healthcare. In this scenario, clinicians can use the health knowledge located in remote servers via the Internet to diagnose their patients. However, the fact that these servers are third party and therefore potentially not fully trusted raises possible privacy concerns. In this paper, we propose a novel privacy-preserving protocol for a clinical decision support system where the patients' data always remain in an encrypted form during the diagnosis process. Hence, the server involved in the diagnosis process is not able to learn any extra knowledge about the patient's data and results. Our experimental results on popular medical datasets from UCI-database demonstrate that the accuracy of the proposed protocol is up to 97.21% and the privacy of patient data is not compromised.

Item Type:	Article
Subjects:	Q Science > QH Natural history > QH301 Biology
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	10 Mar 2014 08:31
Last Modified:	10 Mar 2014 08:31
URII:	http://shdl.mmu.edu.my/id/eprint/5326

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