A Literature Survey on Data Mining Techniques to Predict Lifestyle Diseases
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
Data Mining is the process of extraction hidden patterns from previously unknown and imaginably useful information from huge amount of data. The diagnosis of Disease is one of the major application where data mining tools are showing successful results. Lifestyle Diseases linked with the way people live their life. Heart Disease and Type II Diabetes are the two complex diseases that has impact on our lifestyle. The diagnosis of these diseases is complex task which requires much experience and knowledge. Type II Diabetes is one of the silent killer disease worldwide where as Heart Disease is the major cause of the death all over the world in the last few years. In 2000, India(31.7 million) topped the world with highest number of people with diabetes and it is also predicted that by 2030 type II diabetes may afflict to 79.4 million individuals in India. About 17.5 million people die each year in India form Heart disease. Many researchers are using different data mining tools to help medical professionals in the diagnosis of lifestyle diseases. Researchers reviewed literature on the prediction and diagnosis of heart disease and Type II diabetes by using data mining techniques and applied on healthcare data of patients. This paper highlights the important role played by data mining tools in analysis of huge volume of healthcare related data in prediction and diagnosis of lifestyle diseases.
Authors and Affiliations
Divya Sharma, Anand Sharma, Vibhakar Mansotra
Keywords
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