Visualising a state-wide patient data collection : a case study to expand the audience for healthcare data

This paper describes the application of existing and novel adaptations of visualisation techniques to routinely collected health data. The aim of this case study is to examine the capacity for visualisation approaches to quickly and e ectively inform clinical, policy, and scal decision making to improve healthcare provision. We demonstrate the use of interactive graphics, fluctuation plots, mosaic plots, time plots, heatmaps, and disease maps to visualise patient admission, transfer, in-hospital mortality, morbidity coding, execution of diagnosis and treatment guidelines, and the temporal and spatial variations of diseases. The relative e ectiveness of these techniques and associated challenges are discussed.

Supporting adaptive learning with high level timed petri nets

Supporting adaptive learning is one of the key problems for hypertext-based learning applications. This paper proposed a timed Petri Net based approach that provides adaptation to learning activities by controlling the visualization of hypertext information nodes. Simple examples were given while explaining ways to realize adaptive operations. Future directions were also discussed at the end of this paper.