Automated generation of model-based knowledge acquisition tools
Automated generation of model-based knowledge acquisition tools
Knowledge Acquisition - Special issue on knowledge acquisition for therapy-planning tasks
An Expert System for Assigning Patients into Clinical Trials Based on Bayesian Networks
Journal of Medical Systems
A script-based approach to modifying knowledge-based systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Designing scripts to guide users in modifying knowledge-based systems
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
An integrated environment for knowledge acquisition
Proceedings of the 6th international conference on Intelligent user interfaces
Enhancing Clinical Practice Guideline Compliance by Involving Physicians in the Decision Process
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
A Qualitative Expert System for Clinical Trial Assignment
Proceedings of the Eleventh International Florida Artificial Intelligence Research Society Conference
Boolean Functions
Specification and generation of custom-tailored knowledge-acquisition tools
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
A script-based approach to modifying knowledge bases
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Artificial Intelligence in Medicine
Methodological Review: Formal representation of eligibility criteria: A literature review
Journal of Biomedical Informatics
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The purpose of a clinical trial is to evaluate a new treatment procedure. When medical researchers conduct a trial, they recruit participants with appropriate health problems and medical histories. To select participants, they analyze medical records of the available patients, which has traditionally been a manual procedure. We describe an expert system that helps to select patients for clinical trials. If the available data are insufficient for choosing patients, the system suggests additional medical tests and finds an ordering of the tests that reduces their total cost. Experiments show that the system can increase the number of selected patients. We also present an interface that enables a medical researcher to add clinical trials and selection criteria without the help of a programmer. The addition of a new trial takes 10-20min, and novice users learn the functionality of the interface in about an hour.