Knowledge induction from medical databases with higher-order programming

WSEAS Transactions on Information Science and Applications

Volumn 6, Issue 10, 2009, Pages 1719-1728

  Kerdprasop, Nittaya ^a   Kerdprasop, Kittisak ^a  

^a SURANAREE UNIVERSITY OF TECHNOLOGY   (Thailand)

Author keywords

Higher order programming; Logic based knowledge induction; Medical decision making; Medical informatics

Indexed keywords

CLINICAL DATA; COMPUTATIONAL INTELLIGENCE; DISEASE TREATMENT; DOMAIN SPECIFIC; ELECTRONIC DATA; FLEXIBLE TOOL; HEALTHCARE ORGANIZATIONS; HIGHER ORDER; LOGIC-BASED LANGUAGES; MEDICAL DATA MINING; MEDICAL DATABASE; MEDICAL DECISION MAKING; MEDICAL DECISION SUPPORT SYSTEM; MEDICAL INFORMATICS; MEDICAL PRACTITIONER; META PROGRAMMING; PRE-TREATMENT; PROGRAMMING LOGIC;

ARTIFICIAL INTELLIGENCE; DECISION MAKING; DECISION SUPPORT SYSTEMS; DECISION THEORY; DIAGNOSIS; LINGUISTICS; LOGIC PROGRAMMING; MEDICAL COMPUTING; PATTERN MATCHING;

MEDICAL EDUCATION;

EID: 77953379410     PISSN: 17900832     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (20)

1. R. Agrawal et al., Fast discovery of association rules, In U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy (Eds.), Advances in Knowledge Discovery and Data Mining, AAAI Press, pp. 307-328.
2. Y. Bedard et al., Integrating GIS components with knowledge discovery technology for environmental health decision support, Int. J Medical Informatics, Vol. 70, 2003, pp. 79-94.
3. C. Bojarczuk et al., A constrained-syntax genetic programming system for discovering classification rules: Application to medical data sets, Artificial Intelligence in Medicine, Vol. 30, 2004, pp. 27-48.
4. E. German, A. Leibowitz, and Y. Shahar, An architecture for linking medical decisionsupport applications to clinical databases and its evaluation, J. Biomedical Informatics, Vol. 42, 2009, pp. 203-218.
5. S. Ghazavi and T. Liao, Medical data mining by fuzzy modeling with selected features, Artificial Intelligence in Medicine, Vol. 43, No. 3, 2008, pp. 195-206.
6. M. Huang, M. Chen, and S. Lee, Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis, Expert Systems with Applications, Vol. 32, 2007, pp. 856-867.
7. N. Hulse et al., Towards an on-demand peer feedback system for a clinical knowledge base: A case study with order sets, J Biomedical Informatics, Vol. 41, 2008, pp. 152-164.
8. C.-P. Hung, H.-J. Su, and S.-L. Yang, Melancholia diagnosis based on GDS evaluation and meridian energy measurement using CMAC neural network approach, WSEAS Transactions on Information Science and Applications, 6 (3), March 2009, pp. 500-509.
9. E. Kretschmann, W. Fleischmann, and R. Apweiler, Automatic rule generation for protein annotation with the C4.5 data mining algorithm applied on SWISS-PROT, Bioinformatics, Vol. 17, No. 10, 2001, pp. 920-926.
10. P.-J. Kwon, H. Kim, and U, Kim, A study on the web-based intelligent self-diagnosis medical system, Advances in Engineering Software, Vol. 40, 2009, pp. 402-406.
11. C. Lin et al., A decision support system for improving doctors' prescribing behavior, Expert Systems with Applications, Vol. 36, 2009, pp. 7975-7984.
12. J. MacQueen, Some methods for classification and analysis of multivariate observations, Proceedings of the 5th Berkeley Symp. on Mathematical Statistics and Probability, vol. 1, pp. 281-297.
13. E. Mugambi et al., Polynomial-fuzzy decision tree structures for classifying medical data, Knowledge-Based System, Vol. 17, No. 2-4, 2004, pp. 81-87.
14. G. Nadathur and D. Miller, Higher-order Horn clauses, J ACM, Vol. 37, 1990, pp. 777-814.
15. L. Naish, Higher-order logic programming in Prolog, Technical Report 96/2, Dept. Computer Science, Univ. Melbourne, Australia, 1996.
16. S.-H. Nienhuys-Cheng and R. D. Wolf, Foundations of Inductive Logic Programming, Springer, 1997.
17. B. Pandey and R. B. Mishra, Knowledge and intelligent computing system in medicine, Computers in Biology and Medicine, Vol. 39, 2009, pp. 215-230.
18. J. R. Quinlan, Induction of decision trees, Machine Learning, Vol. 1, 1986, pp. 81-106.
19. O. Rijal et al., A relook at logistic regression methods for the initial detection of lung ailments using clinical data and chest radiography, WSEAS Transactions on Information Science and Applications, 6 (9), September 2009, pp. 1503-1512.
20. T. Wah and O. Sim, Development of a data warehouse for lymphoma cancer diagnosis and treatment decision support, WSEAS Transactions on Information Science and Applications, 6 (3), March 2009, pp. 530-543.