ANALYSIS OF TECHNIQUES USED TO DISCOVER PATTERNS FROM DATASET FOR DISEASE PREDICTION

Disease detection by the use of technology becomes need of the hour. Lack of time and ignorance causes the problems to increase substantially. Historical medical records of persons can be used to analyse the patterns and discover the disease if any or the future outcomes in terms of disease to the person. This paper presents the comprehensive review of techniques under pattern mining used to discover distinct patterns from the given dataset. In addition sequential pattern mining is considered base to predict the diseases and techniques like pattern growth, incremental growth, prefix span etc. are comparatively analysed giving advantages and disadvantages of each. In other words Apriori based algorithms are analysed using proposed literature. Future enhancements are also suggested using the proposed literature.