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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title: Secured Medical Decision Support System based on SVM
Authors Name: Akshay Muley , S. A. Kinariwala
Unique Id: IJSDR1712004
Published In: Volume 2 Issue 12, December-2017
Abstract: The Medical Decision Support System (MDSS), with several data mining techniques that are applied to help doctors diagnose diseases of the patient with similar symptoms, has recently received a great deal of attention. The advantages of the medical decision support system include not only improving diagnostic accuracy but also reducing diagnostic time. In this document, we have proposed the classification of the MDSS with some advanced technologies, such as the Support Vector Machine. The classifier (SVM) offers many advantages over traditional health systems and opens a new way for physicians to forecast the patient's health problems. Specifically, to protect the privacy of historical data of previous patients, a new cryptographic tool called homomorphic additive aggregation scheme (AHPA) was designed. Given that medical care is the field in which the safety of data related to patients' diseases must be preserved, we have used the Pallier Homomorphic encryption technique that substantially fulfills the security objectives. Specifically, with large amounts of clinical data that are generated every day, the classification of support vector machines (SVM) can be used to excavate valuable information to improve the medical decision support system. In this document, we propose the use of the Paillier encryption technique to preserve patient privacy in the cloud. Patient data can be compromised through the cloud. To overcome this scenario, the Homomorphic encryption technique helps. The processing is done in the encrypted data; therefore, there is no possibility of compromising the privacy of the patient's data.
Keywords: Medical Decision Support System, Privacy Preserving, Support Vector Machine, Homomorphic Encryption.
Cite Article: "Secured Medical Decision Support System based on SVM", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.2, Issue 12, page no.27 - 31, December-2017, Available :http://www.ijsdr.org/papers/IJSDR1712004.pdf
Downloads: 000201506
Publication Details: Published Paper ID: IJSDR1712004
Registration ID:170864
Published In: Volume 2 Issue 12, December-2017
DOI (Digital Object Identifier):
Page No: 27 - 31
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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