title: Medical data mining using evolutionary computation.
abstract: In this paper, we introduce a system for discovering medical knowledge by learning Bayesian networks and rules. Evolutionary computation is used as the search algorithm. The Bayesian networks can provide an overall structure of the relationships among the attributes. The rules can capture detailed and interesting patterns in the database. The system is applied to real-life medical databases for limb fracture and scoliosis. The knowledge discovered provides insights to and allows better understanding of these two medical domains.
authors.affiliation: Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong. psngan@cse.cuhk.edu.hk
authors.forename: P S
authors.initials: PS
authors.lastname: Ngan
authors.forename: M L
authors.initials: ML
authors.lastname: Wong
authors.forename: W
authors.initials: W
authors.lastname: Lam
authors.forename: K S
authors.initials: KS
authors.lastname: Leung
authors.forename: J C
authors.initials: JC
authors.lastname: Cheng
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D005260:Female; D006801:Humans; D008297:Male; D016571:Neural Networks, Computer; D012600:Scoliosis