Intelligent visualization and exploration of time-oriented clinical data

We describe a conceptual architecture and software implementation specific to the task of interpretation, summarization, visualization, explanation, and interactive exploration of time oriented clinical data and the multiple levels of meaningful concepts that can be abstracted from these data. We build on our work on abstraction of time oriented clinical data using a knowledge base, acquired from clinical experts, of temporal properties of the data. We call the new framework KNAVE (Knowledge-based Navigation of Abstractions for Visualization and Explanation). The visualization and exploration operators whose semantics are domain independent, access the domain specific knowledge base. Exploration exploits key relations (e.g., the abstraction hierarchy) in each clinical domain. Preliminary assessment of the prototype with several clinical users has been encouraging. The KNAVE methodology has broad ramifications for reducing the load that large numbers of time oriented clinical data put on practising physicians.