G. Ramalingam
Theoretical Computer Science
The information contained in large collections of clinical data can be used for many valuable purposes, such as epidemiological studies, evidence-based medicine, monitoring compliance with best clinical practices, and cost-benefit analyses. However, the emerging standards for the electronic representation of clinical data, such as the Clinical Document Architecture (CDA) [4], are very complex and new tools are required to effectively extract and utilize the information contained in these documents. In this paper, we present HIWAS, a research prototype of a new tool that creates a structural summary of a collection of XML documents, thereby enabling users to find relevant information for a specific purpose within complex XML documents. A HIWAS user can create a target model that contains just the information they need, in a simplified representation that can be queried efficiently and is compatible with existing relational business intelligence technology. By making these complex XML documents digestible with conventional tools, HIWAS lowers a key barrier to meaningful use of aggregated clinical data. © 2011 VLDB Endowment.
G. Ramalingam
Theoretical Computer Science
Xiaozhu Kang, Hui Zhang, et al.
ICWS 2008
Sabine Deligne, Ellen Eide, et al.
INTERSPEECH - Eurospeech 2001
Robert C. Durbeck
IEEE TACON