title: An expert-guided decision tree construction strategy: an application in knowledge discovery with medical databases.
abstract: With the steady growth in electronic patient records and clinical medical informatics systems, the data collected for routine clinical use have been accumulating at a dramatic rate. Inter-disciplinary research provides a new generation of computation tools in knowledge discovery and data management is in great demand. In this study, an expert-guided decision tree construction strategy is proposed to offer an user-oriented knowledge discovery environment. The strategy allows experts, based on their expertise and/or preference, to override inductive decision tree construction process. Moreover, by reviewing decision paths, experts could focus on subsets of data that may be clues to new findings, or simply contaminated cases.
authors.affiliation: Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Y S
authors.initials: YS
authors.lastname: Tsai
authors.forename: P H
authors.initials: PH
authors.lastname: King
authors.forename: M S
authors.initials: MS
authors.lastname: Higgins
authors.forename: D
authors.initials: D
authors.lastname: Pierce
authors.forename: N P
authors.initials: NP
authors.lastname: Patel
mesh_terms: D000465:Algorithms; D019992:Databases as Topic; D003663:Decision Trees; D008722:Methods; D012680:Sensitivity and Specificity