Knowledge Discovery and Knowledge Reuse in Clinical Information Systems

Jon D. Patrick, Leila Safari, and Yuzhong Cheng


Data representation and visualization, Health care information systems, data analytics


Extracting knowledge from data is essential in clinical research, decision making and hypothesis testing. So, providing a general solution to create analytical tools is of prime importance. The objective of this paper is to introduce a special purpose query language, Clinical Data Analytics Language (CliniDAL), based on features in an earlier CliniDAL in which a user can express and can compute answers to any question that is answerable from a CIS. Question and answer categories include point-of-care retrieval queries, descriptive statistics, statistical hypothe-sis testing, scientific experiment complex hypotheses and semantic record retrieval. In addition due to the importance of time in the clinical domain a temporal model is proposed and integrated into CliniDAL. The experimental results reflect the capability of the language in creating desired queries via restricted natural language. Also integrating clinical ontologies like SNOMED helps unifying terminologies of various CISs.

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