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Visual Healthcare Analytics using Adaptive Data Mining

Published on April 2016 by Priyanka B. Shivagunde, Anita R. Kulkarni
National Seminar on Recent Trends in Data Mining
Foundation of Computer Science USA
RTDM2016 - Number 1
April 2016
Authors: Priyanka B. Shivagunde, Anita R. Kulkarni
97dca624-08b9-44b3-8694-8fa74267ed18

Priyanka B. Shivagunde, Anita R. Kulkarni . Visual Healthcare Analytics using Adaptive Data Mining. National Seminar on Recent Trends in Data Mining. RTDM2016, 1 (April 2016), 19-22.

@article{
author = { Priyanka B. Shivagunde, Anita R. Kulkarni },
title = { Visual Healthcare Analytics using Adaptive Data Mining },
journal = { National Seminar on Recent Trends in Data Mining },
issue_date = { April 2016 },
volume = { RTDM2016 },
number = { 1 },
month = { April },
year = { 2016 },
issn = 0975-8887,
pages = { 19-22 },
numpages = 4,
url = { /proceedings/rtdm2016/number1/24682-2571/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Seminar on Recent Trends in Data Mining
%A Priyanka B. Shivagunde
%A Anita R. Kulkarni
%T Visual Healthcare Analytics using Adaptive Data Mining
%J National Seminar on Recent Trends in Data Mining
%@ 0975-8887
%V RTDM2016
%N 1
%P 19-22
%D 2016
%I International Journal of Computer Applications
Abstract

In today's life health care is the very important factor. Each and every day there is new inventions coming out in health care. These inventions provide us new advanced health care services such as new techniques for detection and prevention of diseases and suggestion for new medicines. Detection of disease needs to analyze the biomedical data of human being to classify them into the fit and unfit person with respect to diagnosis of particular disease. There are different classification algorithms in data mining. Till now many researchers have used various algorithms in health care services to increase an accuracy of prediction of diseases. This paper focuses on a proposed system used to detect disease by analyzing symptoms and test reports. It predicts whether the individual has the disease or not. It also gives the stage of the disease the person is suffering from. This system also provides the visualization of the report which helps the patients from the nonmedical background to understand the stage of the diseases. The genetic classification algorithm OlexGA is used for detection of disease and specific stage. The proposed System will work as diagnostic as well as the preventive method for individual. The an important characteristic of the proposed system is its adaptive nature of new symptoms and tests that do not exist in the system. The system is trained automatically to adapt itself to new symptoms and tests of the patients.

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Index Terms

Computer Science
Information Sciences

Keywords

Positive Text Negative Text Symptoms Diagnostic Test Reports Fit Person Unfit Person Carcinoma Cells.