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Publication Type : Journal Article
Publisher : Journal of International Pharmaceutical Research
Source : Journal of International Pharmaceutical Research, Editorial office of Journal of International Pharmaceutical Research, Volume 46, p.529-533 (2019)
Campus : Coimbatore
School : School of Engineering
Department : cyber Security
Year : 2019
Abstract : Background: The big data analytics in health care necessitates the need of security while handling the person specific data obtained through pharmacogenomic as well as deep learning approaches. Secure sharing of data between researchers and medical practitioners can be made by introducing health care security where a platform can be created between the client and the server. Materials and Methods: In this analysis we have developed an early detection tool for ovarian cancer using pharmacogenomic as well as one shot learning algorithm of deep learning technique. Result and Discussion: The model contains a deep CNN Siamese network which was trained using 128093505 parameters with 140 training classes and 14 test classes that showed an accuracy of 86%. Health care security has been applied to this model by using Advanced Encryption Standard(AES), Data Encryption Standard(DES), DNA encryption and a comparative analysis has been carried out among the three where AES was found to be most efficient while considering the crypto ++ 6.0.0 standards. Conclusion: A secure sharing platform has been developed using blockchain technique. © 2019, Editorial office of Journal of International Pharmaceutical Research. All rights reserved.
Cite this Research Publication : M. Abraham, Vyshnavi, A. M. Hima, Srinivasan, C., and Namboori, P. K. Krishnan, “Healthcare security using blockchain for pharmacogenomics”, Journal of International Pharmaceutical Research, vol. 46, pp. 529-533, 2019.