Medical data mining using evolutionary computation

Po Shun NGAN; Man Leung WONG; Wai LAM; Kwong Sak LEUNG; C. Y., Jack CHENG

doi:10.1016/S0933-3657(98)00065-7

Medical data mining using evolutionary computation

Po Shun NGAN, Man Leung WONG, Wai LAM, Kwong Sak LEUNG, C. Y., Jack CHENG

Lingnan College

Research output: Journal Publications › Journal Article (refereed) › peer-review

39 Citations (Scopus)

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
Pages (from-to)	73-96
Number of pages	24
Journal	Artificial Intelligence in Medicine
Volume	16
Issue number	1
DOIs	https://doi.org/10.1016/S0933-3657(98)00065-7
Publication status	Published - 1 May 1999

Funding

This work was partially supported by Hong Kong RGC CERG Grant CUHK 4161/97E and CUHK Engineering Faculty Direct Grant 2050151. The authors wish to thank Chun Sau Lau and King Sau Lee for preparing, analyzing and implementing the rule learning system for the scoliosis database.

Keywords

Bayesian networks
Data mining
Evolutionary computation
Grammar based genetic programming
Rule learning

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10.1016/S0933-3657(98)00065-7

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AU - LEUNG, Kwong Sak

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N2 - 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.

AB - 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.

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KW - Data mining

KW - Evolutionary computation

KW - Grammar based genetic programming

KW - Rule learning

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JF - Artificial Intelligence in Medicine

IS - 1

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Medical data mining using evolutionary computation

Abstract

Funding

Keywords

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