title: A feature dictionary supporting a multi-domain medical knowledge base.
abstract: Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.
authors.affiliation: Illinois Institute of Technology, Department of Computer Science, Chicago 60616.
authors.forename: F
authors.initials: F
authors.lastname: Naeymi-Rad
mesh_terms: D001185:Artificial Intelligence; D001499:Bayes Theorem; D003936:Diagnosis, Computer-Assisted; D004018:Dictionaries, Medical as Topic; D012107:Research Design; D012984:Software; D012985:Software Design