Discovering multifactorial associations with the development of age-related cataract using contrast mining

摘要

Cataract is a cloudiness of eye lens and studies have reported many risk factors for the development of cataract. However, the cumulative effect of multiple factors along with clinical and systemic disease conditions have not been adequately tested due to a limitation in methodology. The collection of a large volume of Electronic Health Records (EHR) offers an opportunity to apply computational tools for knowledge discovery in databases (KDD) process which enable to discover and extract hidden patterns and relationships among a large number of variables. This approach is possible because of the computational friendly EHR database such as the Cerner Health Facts Database. The main goal of this paper is to investigate the factors which are associated with the development of age-related cataracts using EHR data. This study demonstrates the potential of applying data mining tools for risk assessments using large-scale EHR data.