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.
Original language | English |
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Pages (from-to) | 73-96 |
Number of pages | 24 |
Journal | Artificial Intelligence in Medicine |
Volume | 16 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 May 1999 |
Keywords
- Bayesian networks
- Data mining
- Evolutionary computation
- Grammar based genetic programming
- Rule learning