最小Steiner树自动生成SQL查询在病历数据库中的应用

Christopher E. Gillies, Nilesh V. Patel, Gautam B. Singh, S. Kruk, E. Cheng, G. Wilson
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引用次数: 3

摘要

病历数据库的规模和复杂性使得提取信息具有挑战性。由于表有数千个,即使是数据库分析人员也很难找到重要的字段和发现表之间的各种关联。本文介绍了我们在Epic Clarity Reporting数据库中寻找最小Steiner树的初始方法来解决这个问题的一个案例研究。此外,我们还提供了一个web服务体系结构,可用于将我们的方法扩展到多个数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Minimum Steiner Tree for Automatic SQL Query Generation Applied on a Medical Record Database
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.
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