Abstract
Depending on the insured’s age, life insurance companies set the premiums. There are age-slabs for which premiums are set and after a proper medical examination, after a certain age, life insurance is issued. Major insurance company in India such as India Life Insurance Corporation Limited is seeking medical screening for any applicant above 45 years of age. Candidates whose health is not commensurate with age have been observed. This is particularly true of cardiovascular diseases (CVD). Therefore, the same can be tailored for individual candidates based on their medical test history instead of premiums based on age slabs. Checking for CVD, however, requires a number of medical tests, prompting both the applicant and insurance companies to use this method. This can be streamlined by conducting only main medical tests to determine the cardio-vascular system status of the applicant. The paper outlines the primary tests needed to be conducted to assess a person seeking health insurance’s risk of cardiovascular disease. A series of association rules are developed to classify the risk of cardiovascular disease, using three well-proven methods. The three methods are Clustering of K Means, Decision Tree and Logistics Regression. This study suggests that premiums for health insurance should be based on the results of main assessments and their analysis of association rules. The combination of the three methods minimizes the Type 1 error.
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Chaudhuri, A.K., Das, A., Addy, M. (2021). Identifying the Association Rule to Determine the Possibilities of Cardio Vascular Diseases (CVD). In: Hassanien, A., Bhatnagar, R., Darwish, A. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2020. Advances in Intelligent Systems and Computing, vol 1141. Springer, Singapore. https://doi.org/10.1007/978-981-15-3383-9_20
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DOI: https://doi.org/10.1007/978-981-15-3383-9_20
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