Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned
Expert Systems with Applications: An International Journal
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Accruing patients for clinical trials has been a tedious and time consuming task for clinicians. It requires extensive knowledge of the specific criteria for all available clinical trials. Through interviews with clinicians, implications were discovered which reduced the number of required questions/answers to determine eligibility. After gathering and recording data on past breast cancer patients, the answers to the questions asked by an expert system were extracted. An association rule learner, was used to generate implication rules such as: male = not pregnant. It was determined that all current implication rules could be recovered with 100% confidence. Further searching for additional rules resulted in the discovery of several which provided an improvement in the clinical ease of use of the webbased Clinical Trial Assignment Expert System.