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2. [2] Monaco F. Classification of thyroid diseases: suggestions for a revision. J Clin Endocrinol Metab 2003; 88: 1428-1432. [DOI:10.1210/jc.2002-021260] [PMID]

3. [3] Khiew KF, Wang TI, Lin MYS, Jiang Y. Prediction of hypothyroidism disease by data mining technique. J Data Sci 2016; 14: 97-116.

4. [4] Razia S, Narasinga Rao MR. Machine learning techniques for thyroid disease diagnosis - a review. Indian J Sci Technol 2016; 9. [DOI:10.17485/ijst/2016/v9i28/93705]

5. [5] Farhadian M, Mahjub H, Poorolajal J, Moghimbeigi A, Mansoorizadeh M. Predicting 5-year survival status of patients with breast cancer based on supervised wavelet method. Osong Public Health Res Perspect 2014; 5: 324-332. [DOI:10.1016/j.phrp.2014.09.002] [PMID] [PMCID]

6. [6] Kazemi M, Moghimbeigi A, Kiani J, Mahjub H, Faradmal J. Diabetic peripheral neuropathy class prediction by multi category support vector machine model: a cross-sectional study. Epidemiol Health 2016; 38: e2016011. (Persian). [DOI:10.4178/epih.e2016011] [PMID] [PMCID]

7. [7] Aliabadi M, Farhadian M, Darvishi E. Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach. Int Arch Occup Environ Health 2015; 88: :779-787. [DOI:10.1007/s00420-014-1004-z] [PMID]

8. [8] Farhadian M, Salemi F, Saati S, Nafisi N. Dental age estimation using the pulp-to-tooth ratio in canines by neural networks. Imaging Sci Dent 2019; 49: 19-26. [DOI:10.5624/isd.2019.49.1.19] [PMID] [PMCID]

9. [9] Zadeh LA. Fuzzy sets. Information and control. 1965; 8: 338-353. [DOI:10.1016/S0019-9958(65)90241-X]

10. [10] Zadeh LA. The concept of a linguistic variable and its applications to approximate reasoning. Tech Rep Memorandum ERL-M 1973; 411. [DOI:10.1007/978-1-4684-2106-4_1]

11. [11] Krisnaiah V, Srinivas M, Narsimha G, Subhash Chandra N. Diagnosis of heart disease patients using fuzzy classification technique. Int Confer Comput Commun Technol 2014. [DOI:10.1109/ICCCT2.2014.7066746]

12. [12] Mohammadpour RA, Abedi SM, Bagheri S, Ghaemian A. Fuzzy rule-based classification system for assessing coronary artery disease. Comput Math Methods Med 2015; 2015: 564867. [DOI:10.1155/2015/564867] [PMID] [PMCID]

13. [13] Rahmani Katigari M, Ayatollahi H, Malek M, Kamkar Haghighi M. Fuzzy expert system for diagnosing diabetic neuropathy. World J Diabetes 2017; 15: 80-88. [DOI:10.4239/wjd.v8.i2.80] [PMID] [PMCID]

14. [14] Neshat M, Yaghobi M. Designing a Fuzzy expert system of diagnosing the hepatitis B intensity rate and comparing it with adaptive neural network Fuzzy system. Proc World Cong Engin Computer Sci 2009.

15. [15] Doost Hoseini E, Hassanpour-ezatti M, Navidi HR, Abachi T. A Fuzzy expert system for prescribing atorvastatin optimum dose. Koomesh 2012; 13: 43-50.

16. [16] Phuong NH, Kreinovich V. Fuzzy Logic and its Applications in Medicine. Int J Med Inform 2001; 62: 165-173. [DOI:10.1016/S1386-5056(01)00160-5]

17. [17] Asuncion A, Newman D. UCI machine learning repository. 2007.

18. [18] N Assad Sajadi, S Borzouei, H Mahjub, M Farhadian. Diagnosis of hypothyroidism using a fuzzy rule-based expert system. 2018. (In Press). https://doi.org/10.1016/j.cegh.2018.11.007 [DOI:10.1016/j.cegh.2018.11.007.]

19. [19] Vahidi M. Karimi A. Designing an expert system for diagnosis of thyroid disease. 4th international Conference research in science and technology; Saint Petersburg Russia 2016.

20. [20] Baydaa SB Alyas. Design an intelligent system for thyroid diseases diagnosis. Int J Enhanced Res Sci Technol Engin 2014; 4: 217-229.

21. [21] Kesen U, Emre C, Sarıkas A. Generating an artificial intelligent system to diagnosing thyroid gland related diseases using Fuzzy logic and neural network. Acad Plotform 2014.

22. [22] Mohamadi Basatini F, Chinipardaz Z, SeyedTabib M. Determination of thyroid gland state in referrals from Ahvaz university Jah ad laboratory: using multilayer perceptron neural network discrimination in comparing with classical discrimination methods. Jondishapour 2013; 4: 11-21. (Persian).

23. [23] Khanale P, Ambilwade R. A fuzzy inference system for diagnosis of hypothyroidism. J Artific Intell 2011; 4: 45-54. [DOI:10.3923/jai.2011.45.54]

24. [24] Keles A, Keles A. ESTDD: Expert system for thyroid diseases diagnosis. Exp Syst Appl 2008; 34: 242-246. [DOI:10.1016/j.eswa.2006.09.028]

25. [1] Dayan CM. Interpretation of thyroid function tests. The Lancet 2001; 357: 619-624. [DOI:10.1016/S0140-6736(00)04060-5]

26. [2] Monaco F. Classification of thyroid diseases: suggestions for a revision. J Clin Endocrinol Metab 2003; 88: 1428-1432. [DOI:10.1210/jc.2002-021260] [PMID]

27. [3] Khiew KF, Wang TI, Lin MYS, Jiang Y. Prediction of hypothyroidism disease by data mining technique. J Data Sci 2016; 14: 97-116.

28. [4] Razia S, Narasinga Rao MR. Machine learning techniques for thyroid disease diagnosis - a review. Indian J Sci Technol 2016; 9. [DOI:10.17485/ijst/2016/v9i28/93705]

29. [5] Farhadian M, Mahjub H, Poorolajal J, Moghimbeigi A, Mansoorizadeh M. Predicting 5-year survival status of patients with breast cancer based on supervised wavelet method. Osong Public Health Res Perspect 2014; 5: 324-332. [DOI:10.1016/j.phrp.2014.09.002] [PMID] [PMCID]

30. [6] Kazemi M, Moghimbeigi A, Kiani J, Mahjub H, Faradmal J. Diabetic peripheral neuropathy class prediction by multi category support vector machine model: a cross-sectional study. Epidemiol Health 2016; 38: e2016011. (Persian). [DOI:10.4178/epih.e2016011] [PMID] [PMCID]

31. [7] Aliabadi M, Farhadian M, Darvishi E. Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach. Int Arch Occup Environ Health 2015; 88: :779-787. [DOI:10.1007/s00420-014-1004-z] [PMID]

32. [8] Farhadian M, Salemi F, Saati S, Nafisi N. Dental age estimation using the pulp-to-tooth ratio in canines by neural networks. Imaging Sci Dent 2019; 49: 19-26. [DOI:10.5624/isd.2019.49.1.19] [PMID] [PMCID]

33. [9] Zadeh LA. Fuzzy sets. Information and control. 1965; 8: 338-353. [DOI:10.1016/S0019-9958(65)90241-X]

34. [10] Zadeh LA. The concept of a linguistic variable and its applications to approximate reasoning. Tech Rep Memorandum ERL-M 1973; 411. [DOI:10.1007/978-1-4684-2106-4_1]

35. [11] Krisnaiah V, Srinivas M, Narsimha G, Subhash Chandra N. Diagnosis of heart disease patients using fuzzy classification technique. Int Confer Comput Commun Technol 2014. [DOI:10.1109/ICCCT2.2014.7066746]

36. [12] Mohammadpour RA, Abedi SM, Bagheri S, Ghaemian A. Fuzzy rule-based classification system for assessing coronary artery disease. Comput Math Methods Med 2015; 2015: 564867. [DOI:10.1155/2015/564867] [PMID] [PMCID]

37. [13] Rahmani Katigari M, Ayatollahi H, Malek M, Kamkar Haghighi M. Fuzzy expert system for diagnosing diabetic neuropathy. World J Diabetes 2017; 15: 80-88. [DOI:10.4239/wjd.v8.i2.80] [PMID] [PMCID]

38. [14] Neshat M, Yaghobi M. Designing a Fuzzy expert system of diagnosing the hepatitis B intensity rate and comparing it with adaptive neural network Fuzzy system. Proc World Cong Engin Computer Sci 2009.

39. [15] Doost Hoseini E, Hassanpour-ezatti M, Navidi HR, Abachi T. A Fuzzy expert system for prescribing atorvastatin optimum dose. Koomesh 2012; 13: 43-50.

40. [16] Phuong NH, Kreinovich V. Fuzzy Logic and its Applications in Medicine. Int J Med Inform 2001; 62: 165-173. [DOI:10.1016/S1386-5056(01)00160-5]

41. [17] Asuncion A, Newman D. UCI machine learning repository. 2007.

42. [18] N Assad Sajadi, S Borzouei, H Mahjub, M Farhadian. Diagnosis of hypothyroidism using a fuzzy rule-based expert system. 2018. (In Press). https://doi.org/10.1016/j.cegh.2018.11.007 [DOI:10.1016/j.cegh.2018.11.007.]

43. [19] Vahidi M. Karimi A. Designing an expert system for diagnosis of thyroid disease. 4th international Conference research in science and technology; Saint Petersburg Russia 2016.

44. [20] Baydaa SB Alyas. Design an intelligent system for thyroid diseases diagnosis. Int J Enhanced Res Sci Technol Engin 2014; 4: 217-229.

45. [21] Kesen U, Emre C, Sarıkas A. Generating an artificial intelligent system to diagnosing thyroid gland related diseases using Fuzzy logic and neural network. Acad Plotform 2014.

46. [22] Mohamadi Basatini F, Chinipardaz Z, SeyedTabib M. Determination of thyroid gland state in referrals from Ahvaz university Jah ad laboratory: using multilayer perceptron neural network discrimination in comparing with classical discrimination methods. Jondishapour 2013; 4: 11-21. (Persian).

47. [23] Khanale P, Ambilwade R. A fuzzy inference system for diagnosis of hypothyroidism. J Artific Intell 2011; 4: 45-54. [DOI:10.3923/jai.2011.45.54]

48. [24] Keles A, Keles A. ESTDD: Expert system for thyroid diseases diagnosis. Exp Syst Appl 2008; 34: 242-246. [DOI:10.1016/j.eswa.2006.09.028]