Association rule mining and regression support to analysis of dravet syndrome data set

Abstract

The Health Care industry has enormous volume of records and data; however newlinemaximum amount of this data is either properly extracted or analyzed to find newlineout hidden information. There are many challenges and research avenues newlinepresented by many researchers over the two decades to deal with the useful newlinedata available to make meaningful predictions. The growth of information newlinetechnology creates revolution on medical industries to do automatic analysis newlineof disease analysis and diagnosis. To achieve this task, several knowledge newlinediscovery techniques has been used on medical records or data for various newlinetype of disease diagnosis. newlineThe Knowledge Discovery techniques can be applied to determine unknown newlinefrequently occurring patterns which may be efficiently used in the process of newlinedisease diagnosis, so that in turn it will further support the physicians to make newlinedecisions for effective treatment. The generation of association rules with the newlineassociation rule mining technique is the best standard and relevant data newlineextraction method to discover the unknown rules using the medical data set. newlineDravet syndrome is a very seldom ailment which primarily affects the new newlineborn babies between 0 to 12 months. This rare syndrome causes frequent fits newlinewhich affects the brain, in turn the mental and physical stability of the newlinechildren in the above age group. The first part of the proposed work was to identify the various dimensions or newlineattributes that were useful to study, analyze and perform the research for newlineeffective diagnosis of dravet syndrome. The various dimensions were used to newlinedesign the data set for dravet syndrome. This dataset consists of the following newlineinformation such as patient gender, age in months and year, mothers milk feed newlineup to in months, 1st episode of seizure occurrence month, number of visit to newlinehospitals, history of parents having Seizure, season wise seizure occurrence newlinefrequency per day, general reasons for seizure occurrence, general symptoms, newlinetests, seizure type and symptoms, vitamin drugs, seizure drugs, seizure status, newlineIQ level, d