Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor.

ABSTRACT: Healthcare sector is generating a large amount of information corresponding to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for the diagnosis & treatment of disease from the clinical dataset is therefore increasingly becoming necessary. Aim of this study was to assess the applicability of knowledge discovery in brain tumor data warehouse, applying data mining techniques for investigation of clinical parameters that can be associated with occurrence of brain tumor. In this study, a brain tumor warehouse was developed comprising of clinical data for 550 patients. Apriori association rule algorithm was applied to discover associative rules among the clinical parameters. The rules discovered in the study suggests -

SUBMITTER: Sengupta D 

PROVIDER: S-EPMC3717182 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature