Integrating Inductive Knowledge into the Inference System of Biomedical Informatics

This paper presents a new methodology for the design and implementation of the next generation rule-based expert system in a medical domain. In addition to the set of predefined rules, the system includes rules that are automatically induced from the database instances. We design the inductive expert system such that the inductive process has been done through the tree-based knowledge discovery technique. Probabilistic decision rules are then transformed from the induced decision tree. The induced, as well as predefined, rules together form a knowledge base for the inductive expert system. Another feature of our system is the inference engine that can be created automatically. The system is intended to support decision making in biomedical informatics. The general design of our system is, however, appropriate for other domains as well.

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