Discovering knowledge from medical databases using evolutionory algorithms

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@Article{wong:2000:dkm,

• author = "Man Leung Wong and Wai Lam and Kwong Sak Leung and Po Shun Ngan and Jack C. Y. Cheng",
• title = "Discovering knowledge from medical databases using evolutionory algorithms",
• journal = "IEEE Engineering in Medicine and Biology Magazine",
• year = "2000",
• volume = "19",
• number = "4",
• pages = "45--55",
• month = jul # "-" # aug,
• keywords = "genetic algorithms, genetic programming, database management systems, medical databases, knowledge discovery, Bayesian networks, causality relationship models, Bayesian network learning process, continuous variables, advanced evolutionary algorithms, evolutionary programming, learning tasks, fracture database, child fractures, scoliosis database, scoliosis classification, novel clinical knowledge, database errors",
• ISSN = "0739-5175",
• URL = "http://ieeexplore.ieee.org/iel5/51/18543/00853481.pdf",
• size = "11 pages",
• abstract = "Discusses learning roles and causal structures for capturing patterns and causality relationships. The authors present their approach for knowledge discovery from two specific medical databases. First, rules are learned to represent the interesting patterns of the data. Second, Bayesian networks are induced to act as causality relationship models among the attributes. The Bayesian network learning process is divided into two phases. In the first phase, a discretization policy is learned to discretize the continuous variables, and then Bayesian network structures are induced in the second phase. The authors employ advanced evolutionary algorithms such as generic genetic programming, evolutionary programming, and genetic algorithms to conduct the learning tasks. From the fracture database, they discovered knowledge about the patterns of child fractures. From the scoliosis database, they discovered knowledge about the classification of scoliosis. They also found unexpected rules that led to discovery of errors in the database. These results demonstrate that the knowledge discovery process can find interesting knowledge about the data, which can provide novel clinical knowledge as well as suggest refinements of the existing knowledge.",

}

Genetic Programming entries for Man Leung Wong Wai Lam Kwong-Sak Leung Po Shun Ngan Jack Chun-yiu Cheng

Citations