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Designing Medicine Fuzzy Expert System for Diagnosis of Motor System Problems | ||
| Advances in Industrial Engineering | ||
| مقاله 5، دوره 51، شماره 3، دی 2017، صفحه 311-323 اصل مقاله (831.25 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jieng.2017.133763.1005 | ||
| نویسندگان | ||
| Ameneh Khadivar* ؛ Fatemeh Mohammadi Amiri | ||
| Department of Management, Alzahra University, Tehran, Iran | ||
| چکیده | ||
| The purpose of expert systems is to expose the skills of experts to non-specialist people. Late diagnosis of motor system problems can lead to the problems for other parts. Hence, designing a system equipped with the knowledge of the expert who is able to diagnose and treat the diseases appropriately, can provide the patients timely treatment. In this paper, fuzzy expert system for diagnosis and management of motor system problems in wrist, elbow and shoulder have been designed using MATLAB software, and 15 experts knowledge acquisition for diseases diagnosis and treatment, which are the outputs of the Delphi-fuzzy and Delphi methods for diagnosis and treatment, respectively, are stored in the knowledge base of the system as the fuzzy rules. System results show that 86.7 percent of systemic diagnoses are similar to expert diagnosis. The proposed expert system can be used as a scientific source by students. | ||
| کلیدواژهها | ||
| Delphi-fuzzy method؛ Fuzzy Expert System؛ Knowledge acquisition؛ Motor system problems | ||
| مراجع | ||
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1. Singla, J. (2013). “The diagnosis of some lung diseases in a prolog expert system”, International journal of Computer Applications, Vol. 78, No. 15, PP. 37–40.
2. Baghel, K., and Mehta, N. (2015). “A web-based fuzzy expert system for human disease diagnosis”, International Journal of Engineering and Computer Science, Vol. 4, No. 9, PP. 14248–14253.
3. Anto, S., and Chandramathi, S. (2015). “An expert system based on SVM and hybrid GA-SA optimization for hepatitis diagnosis”, International Journal of Computer Engineering in Research Trends, Vol. 2, No. 7, PP. 437–443.
4. Kadhim, M. A., Afshar Alam, M., and Kaur, H. (2011). “Design and implementation of fuzzy expert system of back pain diagnosis”, International Journal of Innovative Technology and Creative Engineering, Vol. 1, No. 9, PP. 16–22.
5. Ayangbekun Oluwafemi, J., and Jimoh Ibrahim, A. (2015). “Expert system for diagnosis neurodegenerative disease”, International Journal of Computer and Information Technology, Vol. 4, No. 4, PP. 694–698.
6. Russell, S., and Norvig, P. (2002). “Artificial intelligence: A modern approach”, Second Edition, Prentice Hall.
7. Khdega, A. Y. G. (2015). “An expert system for diagnosis of ear problems in children”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 4, No. 7, PP. 458–462.
8. Azaab, S., Abu-Naser, S., and Sulisel, O. (2000). “A proposed expert system for selecting exploratory factor analysis procedures”, Journal of the College of Education, Vol. 4, No. 2, PP. 9–26.
9. Beverly, G. H., and Rosewary, H. W. (1994). “An expert support system for service quality improvement”, Proceedings of the Twenty- Seventh Annual Hawaii International Conference on System Science.
10. Abu-Naser, S., Al-Dahdooh, R., Mushtaha, A., and El-Naffar, M. (2010). “Knowledge management in ESMDA: Expert system for medical diagnostic assistance”, ICGST-AIML Journal, Vol. 10, No. 1, PP. 31–40.
11. Salehnia, A., Cong, B., Shin, S., and Alishiri, Z. (1992). “Managerial applications of expert systems languages and tools”, IDEA Group Publishing, USA.
12. Stangerup, S., Tjernstrom, O., Klokker, M., Harcourt, J., and Stokholm, J. (1998). “Point prevalence of barotitis in children and adults after flight, and effect of autoinflation”, Aviation,Space, and Environmental Medicine, Vol. 69, No. 1, PP. 45–49.
13. Ramesh, B. (2009). “Information technology for management”, Tata McGraw-Hill Education Private Limited.
14. Yanagisawa, K., and Kveton, J. F. (1992). “Referred otalgia”, American Journal of Otolaryngol, Vol. 13, No. 6, PP. 323–327.
15. Robinson, J. (2014). “Cold, flu, and cough health center”, WebMD, LLC.
16. Schulze, S. L., Kerschner, J. and Beste, D. (2002). “Pediatric external auditory canal foreign bodies: A review of 698 cases”, Otolaryngol Head and Neck Surgery, Vol. 127, No. 1, PP. 73–78.
17. Mir Anamul, H., Sher-E-Alam, KH., and chowdhury, A. R. (2010). “Human disease diagnosis using a fuzzy expert system”, Journal of Computing, Vol. 2, No. 6, PP. 66–70.
18. Biswas, D., Bairagi, S., Panse, N., and Shinde, N. (2011). “Disease diagnosis system”, International Journal of Computer Science and Informatics, Vol. 1, No. 2, PP. 48–51.
19. Adeli, A., and Neshat, M. (2010). “A fuzzy expert system for heart disease diagnosis”, Proceedings of International Multi-Conference of Engineers and Computer Scientists, Vol. 1, IMECS2010, March 17–19, Hong Kong.
20. Lee, Ch. Sh., Member, S. and Wang, M. H. (2011). “A fuzzy expert system for diabetes decision support application”, Man, and Cybernetics – Part B: Cybernetics, IEEE Transactions on Systems, Vol. 41, No. 1, PP. 139–153.
21. Jain, V., and Raheja, S. (2015). “Improving the prediction rate of diabetes using fuzzy expert system”, International Journal Information Technology and Computer Science, Vol. 10, PP. 84–91.
22. http://in.mathworks.com/help/fuzzy/types-of-fuzzy-inference-systems.html
23. Jafari, N., and Montazer, Gh. A. (2007). “Using Delphi fuzzy method to determine tax policy for country”, Institute for Humanities and Cultural Studies, Humanities Portal, 5.
24. Cheng, Ch., and Lin, Y. (2002). “Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation.” European Journal of Operational Research, No. 142, P.147. | ||
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