Skip navigation


Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3429
Full metadata record
DC FieldValueLanguage
dc.contributor.authorShitole, Manodnya A.-
dc.date.accessioned2022-08-25T09:22:09Z-
dc.date.available2022-08-25T09:22:09Z-
dc.date.issued2016-09-05-
dc.identifier.urihttp://192.168.3.232:8080/jspui/handle/123456789/3429-
dc.description.abstractIn the advanced age in which the healthcare area is exploring widely in that Clinical decision support system, which uses advanced data mining techniques to help clinician make proper decisions, has received considerable attention recently. The advantages of clinical decision support system include not only improving diagnosis accuracy but also reducing diagnosis time. The large data id generated in the healthcare system time by time so every patient is provided their personal information to the doctor for making the decision but because the privacy is the major issue for healthcare system of patient. The requirement is to provide the security to the patient data from unauthorized use the privacy preserving clinical decision support system is given in the system. So in the proposed system the patient security is the main part and in that provided the security to the patient by giving the restriction to the doctor accession. In that we check the authorization of the doctor with the OTP generation because of that the data is preserved. And also the effective Naive Bayesian classification use for the patient easiness for getting the results from the doctor about the disease diagnosis also one prominent part provided in this that patient can upload the document of their so doctor will get help to diagnosis the patient.en_US
dc.titlePatient-Centric and Privacy Preserving Clinical Decision Support System Using Naive Bayesian Classificationen_US
Appears in Collections:Survey: Techniques Of Data Mining For Clinical Decision Support System

Files in This Item:
File Description SizeFormat 
IJSRET_paper.pdf507.81 kBUnknownView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.