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S. Rajesh, G. Barani, V. Suganya, K. Seenthamarai

Published in: International Journal of Current Engineering And Scientific Research ( IJCESR)
Volume- 4, Issue-9, pp.5-8, Sep 2017
DPI :-> 16.10046.IJCESR.2017.V4I9.58.1954

One of the ultimate goals of life science is to improve our understanding of the processes related to disease. General health examination is an integral part of healthcare in many countries. Identifying the patients at risk is important for early warning and preventive intervention. The fundamental challenge of learning a classification model for risk prediction lies in the collected dataset. Particularly, the collected dataset describes the participants in health examinations whose health related conditions can vary greatly from being healthy to being ill. There is no ground truth for differentiating their states of health. Confidentiality agreements with doctors and patients are also required to obtain patient records. In practice, however, there are many obstacles in the collected dataset because of the limitations of time, cost, and confidentiality conflicts. In this project, We propose an interactive system to predict the patient risks of suffering from certain diseases from the collected dataset by using clustering and classification techniques and thereby giving early warning, and preventive intervention to the patients. This dataset is collected from annual general health checkups. This helps to save many lives by predicting the disease at an early stage and thereby reducing the cost of medical expenses

Key-Words / Index Term
Health examination, early warning, Cluster and Classification Techniques, Medical Expenses, HER, Mining, Support Vector Machines.

How to cite this article
S. Rajesh, G. Barani, V. Suganya, K. Seenthamarai , “DISEASE DETECTION BASED ON GRAPH AND DATA CLASSIFICATION”, International Journal of Current Engineering And Scientific Research ( IJCESR), 4, Issue-9, pp.5-8, Sep 2017. DPI:16.10046.IJCESR.V4.I9.1954