Discovering the Patterns of Lung Function Using a Custom Expert Knowledge Acquisition System
The aim of this study was to develop a web-based expert knowledge acquisition system (MCRDR) to provide automatic classification of lung function tests, provide an interrogative tool to assist experts explore a large database of patient cases to discover and evaluate new knowledge, and to test research hypotheses. The expert system acquires knowledge incrementally as the expert uses the system and compiles a set of linked rules. The web-based system is now fully developed and ready to receive both archived and prospective lung function test results from several respiratory laboratories in Australia.
Our PhD student, Tristan Ling, who won an APA scholarship to undertake this project, conducted this work.
The results of this research were presented at international scientific conferences in Australia and Korea.
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Staff
Team Members
- Professor Haydn Walters (Senior Member)