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Reseach Article

Remedy Selection based on Artificial Intelligent Methods

by Saeedeh Sadat Sadidpour, Saeed Shiry Ghidary
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 19 - Number 9
Year of Publication: 2011
Authors: Saeedeh Sadat Sadidpour, Saeed Shiry Ghidary
10.5120/2392-2919

Saeedeh Sadat Sadidpour, Saeed Shiry Ghidary . Remedy Selection based on Artificial Intelligent Methods. International Journal of Computer Applications. 19, 9 ( April 2011), 6-9. DOI=10.5120/2392-2919

@article{ 10.5120/2392-2919,
author = { Saeedeh Sadat Sadidpour, Saeed Shiry Ghidary },
title = { Remedy Selection based on Artificial Intelligent Methods },
journal = { International Journal of Computer Applications },
issue_date = { April 2011 },
volume = { 19 },
number = { 9 },
month = { April },
year = { 2011 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume19/number9/2392-2919/ },
doi = { 10.5120/2392-2919 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:06:30.249500+05:30
%A Saeedeh Sadat Sadidpour
%A Saeed Shiry Ghidary
%T Remedy Selection based on Artificial Intelligent Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 19
%N 9
%P 6-9
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Homeopathy decision is a decision under uncertainty and an essential activity for accurate treatment. Expert systems have long history of application in medical diagnosis. In this paper we study application of Fuzzy Expert System and decision tree for selection of suitable remedy in Homeopathy. A decision made by Homeopath is highly dependent on the quality of selected rubrics. The rubrics are collected during case taking and generally contains expressions that might be considered fuzzy, such as ‘never’, ‘sometimes’, ‘always’, and so on, making it difficult to model them with conventional computational methods. In this context, fuzzy set theory in expert systems is an interesting tool to deal with the representation of inaccurate medical entities. Hence, we can go from natural language (linguistic variables) to numerical variables which are more convenient to handle in a computer. The proposed method reduces sensitivity of system to homeopath mistakes and increase security of system.

References
  1. I. V. Polony, "The use of manual and computer aided search methods in the homeopathic repertory," AEON GROUP, pp. 1-6, 2005.
  2. "Readings in machine learning," J. W. Shavlik and T. G. Dietterich, Eds., ed: Morgan Kaufmann Publishers, San Mateo, California, 1990.
  3. I. Kononenko, "Machine learning for medical diagnosis: history, state of the art and perspective," Artificial Intelligence in Medicine, vol. 23, pp. 89-109, 2001.
  4. I. Kononenko, et al., "Application of machine learning to medical diagnosis," in Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, et al., Eds., ed: John Wiley & Sons Ltd, 1997.
  5. M. A. M. Reis, et al., "Fuzzy expert system in the prediction of neonatal resuscitation," Brazilian Journal of Medical and Biological Research, vol. 37, pp. 755-764, 2004.
  6. H. Teodorescu, et al., "Fuzzy and Neuro-Fuzzy Systems in Medicine," CRC Press, Boca Raton, FL, USA, 1999.
  7. K. P. Adlassnig, "A fuzzy logical model of computer-assisted medical diagnosis," Methods Inf Med, vol. 19, pp. 141-148, 1980.
  8. G. Vithoulkas. The Vithoulkas Expert System (V.E.S.).
  9. (2011). Decision tree learning. Available: http://en.wikipedia.org/wiki/
  10. L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, pp. 338-353, 1965.
  11. D. M. Velasevic, et al., "A fuzzy sets theory application in determining the severity of respiratory failure," International Journal of Medical Informatics, vol. 63, pp. 101-107, 2001.
  12. G. J. Klir and T. A. Folger, Fuzzy Sets, Uncertainty, and Information. Englewood Cliffs, NJ: Prentice Hall, 1988.
  13. W. Pedrycz and F. Gomide, An Introduction to Fuzzy Sets: Analysis and Design. Massachusetts, London: A Bradford Book, The MIT Press Cambridge, 1998.
  14. (2011). Fuzzy Expert Systems. Available: http://www.austinlinks.com/Fuzzy/expert-systems.html
Index Terms

Computer Science
Information Sciences

Keywords

Intelligent diagnosis Decision Tree Fuzzy Expert System Homeopathy Remedy Determination