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An Integrated Approach for Cancer Disease Risk Assessment using Attribute Dependency Mining

Author(s):

Satyam Shukla , KNIT Sultanpur; Dharmendra Lal Gupta, KNIT Sultanpur

Keywords:

Cancer, Horizontal Clustering, Vertical clustering, Intuitionistic Fuzzy Set, Point Energy, cluster energy

Abstract

In current era, one of the main concern or we can say that major issue is related to proper healthcare services. Unlike previous works, this research work is carried out for cancer disease risk assessment using several data mining techniques. Since cancer is the most deadly disease so properly diagnosing cancer and its risk before its onset is utmost need of the present time and data mining can significantly effective in this regard. Previous researchers however used data mining tools to diagnose cancer after it has already affected the patient. To effectively analyze and to extract key hidden knowledge and pattern from a voluminous medical data, advance researchers in data mining have become a key player in health care industries. The main objective of this paper is to give better and timely treatment, diagnosis and preventive measures at early stage of cancer patients so that the situation does not become critical. The proposed approach collect all the details of patient and this approach identify and classify the patients into different classes from high to low risk. The proposed research work is based on the result of different attributes like BMI, location age, gender and dependency between the attributes.

Other Details

Paper ID: IJSRDV4I80284
Published in: Volume : 4, Issue : 8
Publication Date: 01/11/2016
Page(s): 572-577

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