title: Exploring a new best information algorithm for Iliad.
abstract: Iliad is a diagnostic expert system for internal medicine. One important feature that Iliad offers is the ability to analyze a particular patient case and to determine the most cost-effective method for pursuing the work-up. Iliad's current "best information" algorithm has not been previously validated and compared to other potential algorithms. Therefore, this paper presents a comparison of four new algorithms to the current algorithm. The basis for this comparison was eighteen "vignette" cases derived from real patient cases from the University of Utah Medical Center. The results indicated that the current algorithm can be significantly improved. More promising algorithms are suggested for future investigation.
authors.affiliation: University of Utah, Department of Medical Informatics.
authors.forename: D
authors.initials: D
authors.lastname: Guo
authors.forename: M J
authors.initials: MJ
authors.lastname: Lincoln
authors.forename: P J
authors.initials: PJ
authors.lastname: Haug
authors.forename: C W
authors.initials: CW
authors.lastname: Turner
authors.forename: H R
authors.initials: HR
authors.lastname: Warner
mesh_terms: D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D005103:Expert Systems; D007257:Information Theory; D007388:Internal Medicine; D008962:Models, Theoretical; D011336:Probability