Minimum Steiner Tree for Automatic SQL Query Generation Applied on a Medical Record Database

Abstract

The size and complexity of medical record databases makes extracting information challenging. With the tables numbering in thousands, even database analysts have trouble finding important fields and discovering various associations between tables. This paper presents a case study of our initial method of finding minimum Steiner trees in the Epic Clarity Reporting database to solve this problem. In addition, we present a web service architecture that can be used to extend our approach to multiple databases.