| A diagnostic system based on a multi-decision approximate rules model |
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Symposium on Applied Computing
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Proceedings of the 1997 ACM symposium on Applied computing
table of contents
San Jose, California, United States
Pages: 20 - 24
Year of Publication: 1997
ISBN:0-89791-850-9
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Authors
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Ray R. Hashemi
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Department of Computer and Information Science, University of Arkansas at Little Rock, Little Rock, AR and Division of Nerotoxicology, National Center for Toxicological Research/FDA, Jefferson, AR
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Fred Choobineh
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Department of Industrial Engineering, University of Nebraska at Lincoln, Lincoln, NE
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John Talburt
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Department of Computer and Information Science, University of Arkansas at Little Rock, Little Rock, AR
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William Slikker
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Division of Nerotoxicology, National Center for Toxicological Research/FDA, Jefferson, AR
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Merle G. Paule
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Division of Nerotoxicology, National Center for Toxicological Research/FDA, Jefferson, AR
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Downloads (6 Weeks): 1, Downloads (12 Months): 17, Citation Count: 0
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REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Berenji H. R., "Machine Learning in Fuzzy Control", Int. Conference on Fuzzy Logic & Neural Networks, lizuka, Fukuoka, Japan, pp 231-234, 1990.
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Grzymala-Busse J. W., "The Rule Induction System LERS Q: A Version for Personal Computers", Proc. of The Intl. Workshop on Rough Sets and Knowledge Discovery, Baniff, Alberta, Canada, pp 509, 1993.
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Ray R. Ashemi , Mehdi Razzaghi , Frederick R. Jelovsek , John R. Talburt, Conflict resolution in inductive learning from examples, Proceedings of the 1992 ACM/SIGAPP Symposium on Applied computing: technological challenges of the 1990's, p.598-602, April 1992, Kansas City, Missouri, United States
[doi> 10.1145/143559.143696]
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Hashemi R. R., Jelovsek F. R., Razzaghi M., "Developmental Toxicity Risk Assessment: A Rough Sets Approach", Intl. J. of Methods of Information in Medicine, 32: 47-54, 1993.
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Hashemi R. R., Pearce B. A., Hinson W. G., Paule M. G., and Young J. F., "IQ Estimation of Monkeys Based on Human Data Using Rough Sets", Proc. of The Intl. Workshop on Rough Sets and Soft Computing, San Jose, California, pp 400-407, 1994.
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Ray Hasemi , Bruce A. Pearce , Ramin B. Arani , William G. Hinson , Merle G. Paule, A rough-genetic approach for classification of complex data, Proceedings of the 1996 ACM symposium on Applied Computing, p.282-288, February 17-19, 1996, Philadelphia, Pennsylvania, United States
[doi> 10.1145/331119.331194]
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Hashemi R. R., Pearce B. A., Arani R. B., Hinson W. G., and Paule M. G., "A Fusion of Rough Sets, Modified Rough sets, and Genetic Algorithms for Hybrid Diagnostic Systems", Rough Sets and DataMining: Analysis of Imprecise Data, Kluwer Academic Publishers, Boston, 1997, pp 149-176.
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Michalski R., "A theory and Methodology of Inductive Leaming", Machine Learning, Palo Alto: Tioga Publishing Company 1983, pp 83 - 134.
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Paule, M.G., Cranmer, j.M., Wilkins, J.D., Stern, H.P., and Hoffman, E.L., "Quantitation of Complex Brain Function in Children: Preliminary Evaluation Using a Nonhuman Primate Behavioral Test Battery", Neurotoxicology 9(3): 367-378, 1988.
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Quinlan R. J., ~Discovering Rule by Induction From Large Collections of Examples~, Expert Systems in the Micro-Electronic Age, Edinburg University Press, Edinburg, pp 168-201, 1979.
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INDEX TERMS
Primary Classification:
G.
Mathematics of Computing
G.2
DISCRETE MATHEMATICS
Additional Classification:
H.
Information Systems
H.4
INFORMATION SYSTEMS APPLICATIONS
H.4.2
Types of Systems
Subjects:
Decision support (e.g., MIS)
I.
Computing Methodologies
I.2
ARTIFICIAL INTELLIGENCE
I.2.1
Applications and Expert Systems
Subjects:
Medicine and science
I.2.4
Knowledge Representation Formalisms and Methods
Subjects:
Representations (procedural and rule-based)
J.
Computer Applications
J.3
LIFE AND MEDICAL SCIENCES
Subjects:
Health
General Terms:
Algorithms,
Design,
Human Factors,
Management,
Measurement,
Performance,
Theory
Keywords:
approximate rule,
diagnostic system,
modified rough sets,
multi-decision approximate rule,
rough sets
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