Clinical Decision Support System for Privacy Preserving using Information Retrieval

Ms. Pradnya Kul; Dr. V. S. Bidve

doi:https://doi.org/10.14445/22315381/IJETT-V48P258

Research Article | Open Access | Download PDF

Volume 48 | Number 3 | Year 2017 | Article Id. IJETT-V48P258 | DOI : https://doi.org/10.14445/22315381/IJETT-V48P258

Clinical Decision Support System for Privacy Preserving using Information Retrieval

Ms. Pradnya Kul, Dr. V. S. Bidve

Citation :

Ms. Pradnya Kul, Dr. V. S. Bidve, "Clinical Decision Support System for Privacy Preserving using Information Retrieval," International Journal of Engineering Trends and Technology (IJETT), vol. 48, no. 3, pp. 326-330, 2017. Crossref, https://doi.org/10.14445/22315381/IJETT-V48P258

Abstract

In this paper, the proposed system is designed which predicts the accurate disease and prevention. Information retrieval techniques are used such as data cleaning, data smoothing, data clustering to get the data required for prediction. To get accurate prediction and prevention of disease K-means algorithm is used in the system. It basically partitions the data into cluster and then finds the result. In addition performance criteria via extensive simulation also demonstrate that the system can effectively calculate patient’s disease risk with high accuracy in privacy preserving way. All this data is stored in cloud with encryption technique. So result for privacy preserving is more accurate.

Keywords

Clinical decision Support System, Patient centric, Naive Bayesian classifier, K-means clustering, AWS S3

References

[1] R. Bellazzi and B. Zupan, ?Predictive data mining in clinical medicine: current issues and guidelines,? International journal of medical informatics, vol. 77, no. 2, pp. 81–97, 2008.
[2] Y. Rahulamathavan, S. Veluru, R. Phan, J. Chambers, and M. Rajarajan, ?Privacy-preserving clinical decision support system using Gaussian kernel based classification,? IEEE Journal of Biomedical and Health Informatics, pp. 56–66, 2014.
[3] Y. Tong, J. Sun, S. S. M. Chow, and P. Li, ?Cloud-assisted mobile-access of health data with privacy and auditability,? IEEE J. Biomedical and Health Informatics, vol. 18, no. 2, pp. 419– 429, 2014.
[4] R. Lu, H. Zhu, X. Liu, J. K. Liu, and J. Shao, ?Toward efficient and privacy-preserving computing in big data era,? IEEE Network, vol. 28, no. 4, pp. 46–50, 2014.
[5] H. Monkaresi, R. A. Calvo, and H. Yan, ?A machine learning approach to improve contactless heart rate monitoring using a webcam,? IEEE J. Biomedical and Health Informatics, vol. 18, no. 4, pp. 1153–1160, 2014.
[6] J.-P. Hubaux, J. Fellay, E. Ayday, M. Laren, J. L. Raisaro, P. Jack et al., ?Privacy-preserving computation of disease risk by using genomic, clinical, and environmental data,? in Proceedings of USENIX Security Workshop on Health Information Technologies (HealthTech? 13), no. EPFL-CONF-187118, 2013.
[7] Ximeng Liu, Student Member, IEEE, Rongxing Lu, Member, IEEE, Jianfeng Ma, Member, IEEE, Le Chen, and Baodong Qin ? Privacy-Preserving Patient-Centric Clinical Decision Support System on Na¨?ve Bayesian Classification ?, IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. XX, NO. XX, DECEMBER2016.
[8] M.Parvathavarthini , E.Ramara "Multilink Constrained k-means Clustering Algorithm for Information Retrieval", International Journal of Engineering Trends and Technology (IJETT), V13(3),140-143 July 2014. ISSN:2231-5381