INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Secured Medical Decision Support System based on SVM
Authors Name:
Akshay Muley
, S. A. Kinariwala
Unique Id:
IJSDR1801001
Published In:
Volume 3 Issue 1, January-2018
Abstract:
The Secure Medical Decision Support System (SMDSS), which employs several data mining techniques, is used to help diagnose and treat patients with similar symptoms. The advantages of safe decision support systems include not only privacy preservation but also improves diagnostic accuracy. It also reduces the diagnostic time. To speed up the diagnosis and improve the accuracy of the diagnosis in the current health care system, it is important to make the diagnosis faster and cheaper. This system is called Secure Medical Decision Support System (SMDSS). The data mining techniques used to assist physicians in diagnosing patients with similar symptoms have been very popular in recent years. Past The advantages of medical decision support systems include improved diagnostic accuracy. It also reduces the diagnostic time. In this article, we use the Support Vector Machine (SVM) mining technique, which is used as a classifier that has advantages over traditional mining methods and is a new way of predicting a patient's disease. Because the system was built on the cloud platform, it was necessary to add some features that meet the security requirements. Particularly with the many data related to health care being created daily, the classification can be used to dig up valuable information to improve medical decision support systems. Homomorphic cryptographic techniques are useful for keeping the privacy of the patient in the cloud. Here, using the SVM Classifier and Encryption Techniques, and trying to make the clinical decision support system more useful in providing some important, accurate and effective death information.
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.3, Issue 1, page no.1 - 7, January-2018, Available :http://www.ijsdr.org/papers/IJSDR1801001.pdf
Downloads:
000337064
Publication Details:
Published Paper ID: IJSDR1801001
Registration ID:170886
Published In: Volume 3 Issue 1, January-2018
DOI (Digital Object Identifier):
Page No: 1 - 7
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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