This paper describes about the problem on estimation of disease risks with a large health checkup database. The proposed method uses a naive Bayesian classifier with the extension of two dimensional kernel density estimation technique. The framework is tested by estimation of disease risks for examinee with three diseases, hypertension, diabetes and dyslipidemia. Combination of attribute interactions and naive Bayesian method shows considerable improvement in estimation experiments.
