title: Automated acquisition of rules from clinical databases and its evaluation.
abstract: This paper presents an approach to induction of rules from databases using rough set model. The system was evaluated on three clinical databases, and induced results were compared with other conventional rule induction methods and medical experts' rules. The results show that the introduced results outperforms other methods, but that the description length of induced rules is a little short, compared with that of experts' rules, which suggests that experts' rules are combination of different kinds of reasoning, rather than simple classification.
authors.affiliation: Department of Information Medicine, Tokyo Medical and Dental University, Japan.
authors.forename: S
authors.initials: S
authors.lastname: Tsumoto
authors.forename: H
authors.initials: H
authors.lastname: Tanaka
mesh_terms: D000465:Algorithms; D002965:Classification / Q000379:methods*; D003628:Database Management Systems; D019992:Databases as Topic; D005069:Evaluation Studies as Topic; D005103:Expert Systems; D006801:Humans; D007257:Information Theory; D011336:Probability