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A hybrid system applied to epidemic screening
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Artificial IntelligenceEngineeringModel-based ReasoningIntelligent SystemsKnowledge-based ReasoningComplex Problem SolvingInfectious Disease ModellingData ScienceMedical Expert SystemQuantitative Mbr SystemHybrid SystemInfectious Disease EpidemiologyKnowledge RepresentationDeductive Rbr SystemCase-based ReasoningKnowledge DiscoveryDecision Support SystemsDisease SurveillanceComputer ScienceEpidemiologyReasoningAutomated ReasoningRule InductionBusinessEpidemic IntelligenceHealth Informatics
Although many knowledge‐based systems (KBSs) focus on single‐paradigm approaches to encoding knowledge (such as production rules), human experts rarely use a single type of knowledge to solve a real‐world problem. A human expert usually combines a number of reasoning mechanisms. In recent years, rule‐based reasoning (RBR), case‐based reasoning (CBR) and model‐based reasoning (MBR) have emerged as important and complementary reasoning methodologies in the intelligent systems area. For complex problem solving, it is useful to integrate RBR, CBR and MBR. In this paper, a hybrid epidemic screening KBS which integrates a deductive RBR system, an inductive CBR system and a quantitative MBR system is proposed. The system has been tested using real epidemic screening variables and data.