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Research Article

JCR. 2020; 7(9): 3354-3360

An Efficient and Privacy-Preserving Disease Risk Prediction Scheme for E-Healthcare


Data analysis plays a significant role in handling a large amount of data in the healthcare. The previous
medical researches based on handling and assimilate a huge amount of hospital data instead of prediction. Due to an
enormous amount of data growth in the biomedical and healthcare field the accurate analysis of medical data
becomes propitious for earlier detection of disease and patient care. With the development of society and economy,
people pay more attention to their own health. The demand of more personalized health service is gradually rising.
However, due to the lack of experienced doctors and physicians, most healthcare organizations cannot meet the
medical demand of public. Due to that public want the Medical Treatment online with accuracy. Now a day’s,
public has no time to get the doctor physically, and then search the online hospital near about the current location.
With the widespread use of hospital information system, there is huge amount of generated data which can be used
to improve healthcare service. Thus, more and more data mining applications are developed to provide people more
customized healthcare service. In the proposed paper we use different algorithm to increase the security of sensitive
information of hospital management includes doctors, patients and so on.

Key words: Disease prediction, Security, Data Mining, Healthcare service, Hospital management

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