Managing Theoretical Single-Disease Guideline Recommendations for Actual Multiple-Disease Patients
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Situations managed by clinical practice guidelines (CPGs) usually correspond to general descriptions of theoretical patients that suffer from only one disease in addition to the specific pathology CPGs focus on. When building knowledge bases, the lack of decision support for complex multiple-disease patients is usually transferred to computer-based systems. Starting from a GEM-encoded instance of CPGs, we developed a module that automatically generated IF-THEN-WITH decision rules. A two-stage unification process has been implemented. All the rules whose IF-part was in partial matching with a patient clinical profile were triggered. A synthesis of triggered rules has then been performed to eliminate redundancies and incoherence. All remaining, eventually competitive, recommendations are finally displayed to physicians leaving them the control and the responsibility of handling the controversy and thus the opportunity to make informed decisions.
KeywordsInference Engine Partial Match Relevant Recommendation Trigger Rule Numerous Disorder
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