Abstract
In this paper, we use fuzzy reasoning techniques and the domain ontology for anti-diabetic drugs selection. We present an anti-diabetic drugs recommendation system based on fuzzy rules and the anti-diabetic drugs ontology to recommend the medicine and the medicine information. The experimental results show that the proposed anti-diabetic drugs recommendation system has a good performance for anti-diabetic drugs selection.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bobillo, F., Delgado, M., Gómez-Romero, J., López, E.: A Semantic Fuzzy Expert System for a Fuzzy Balanced Scorecard. Expert Systems with Applications 36(1), 423–433 (2009)
Chen, S.M., Lee, S.H., Lee, C.H.: A New Method for Generating Fuzzy Rules from Numerical Data for Handling Classification Problems. Applied Artificial Intelligence 15(7), 645–664 (2001)
Lee, C.C.: Fuzzy Logic in Control Systems: Fuzzy Logic Controller, Part II. IEEE Transactions on Systems, Man, and Cybernetics 20(2), 419–435 (1990)
Lee, C.S., Wang, M.H.: A Fuzzy Expert System for Diabetes Decision Support Application. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 41(1), 139–153 (2011)
Lee, C.S., Wang, M.H., Hagras, H.: A Type-2 Fuzzy Ontology and Its Application to Personal Diabetic-Diet Recommendation. IEEE Transactions on Fuzzy Systems 18(2), 374–395 (2010)
Lee, C.S., Jian, Z.W., Huang, L.K.: A Fuzzy Ontology and Its Application to News Summarization. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 35(5), 859–880 (2005)
Misra, S., Roy, S., Obaidat, M.S., Mohanta, D.: A Fuzzy Logic-Based Energy Efficient Packet Loss Preventive Routing Protocol. In: Proceedings of the 12th International Conference on Symposium on Performance Evaluation of Computer & Telecommunication Systems, SPECTS 2009, pp. 185–192 (2009)
Mao, Y., Wu, Z., Tian, W., Jiang, X., Cheung, W.K.: Dynamic Sub-Ontology Evolution for Traditional Chinese Medicine Web Ontology. Journal of Biomedical Informatics 41(5), 790–805 (2008)
Quan, T.T., Hui, S.C., Fong, A.C.M.: Automatic Fuzzy Ontology Generation for Semantic Help-Desk Support. IEEE Transactions on Industrial Informatics 2(3), 1551–3203 (2006)
Rodbard, H.W., Blonde, L., Braithwaite, S.S., Brett, E.M., Cobin, R.H., Handelsman, Y., Hellman, R., Jellinger, P.S., Jovanovic, L.G., Levy, P., Mechanick, J.I., Zangeneh, F.: American Association of Clinical Endocrinologists Medical Guidelines for Clinical Practice for the Management of Diabetes Mellitus. American Association of Clinical Endocrinologists 13, 1–68 (2007)
Shortliffe, E.H.: MYCIN: A Rule-Based Computer Program for Advising Physicians Regarding Antimicrobial Therapy Selection. Technical Report, Department of Computer Sciences, Stanford University, California (1974)
Zadeh, L.A.: Fuzzy Sets. Information and Control 8, 338–353 (1965)
Joseki - A SPARQL Server for Jena, http://joseki.sourceforge.net/
OWL Web Ontology Language Overview, http://www.w3.org/TR/owl-features
Ontology, http://en.wikipedia.org/wiki/Ontology
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, SM., Huang, YH., Chen, RC., Yang, SW., Sheu, TW. (2012). Using Fuzzy Reasoning Techniques and the Domain Ontology for Anti-Diabetic Drugs Recommendation. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7196. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28487-8_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-28487-8_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28486-1
Online ISBN: 978-3-642-28487-8
eBook Packages: Computer ScienceComputer Science (R0)