title: Automated transformation of probabilistic knowledge for a medical diagnostic system.
abstract: Iliad is a large medical diagnostic system that covers more than 2000 diagnoses and 9000 findings. Due to the size and the complexity of this system, a robust knowledge representation is essential to consistently and efficiently model the medical knowledge involved. In this paper, we describe the knowledge representation currently used in Iliad and a probabilistic representation based on the Bayesian network formalism which can be derived using the information that the Iliad knowledge base contains.
authors.affiliation: Department of Medical Informatics, University of Utah, Salt Lake City.
authors.forename: Y C
authors.initials: YC
authors.lastname: Li
authors.forename: P J
authors.initials: PJ
authors.lastname: Haug
authors.forename: H R
authors.initials: HR
authors.lastname: Warner
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001499:Bayes Theorem; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D016571:Neural Networks, Computer