Decision Making Based on Fuzzy Aggregation Operators for Medical Diagnosis from Dental X-ray images
Tác giả
Tài liệu tham khảo
[1] Ahn, J. Y., Han, K. S., Oh, S. Y., and Lee, C. D., An application of interval-valued intuitionistic fuzzy sets for medical diagnosis of headache. Int. J. Innov. Comput. Inf. Control 7(5):2755–2762, 2011.
[2] Al-Shayea, Q. K., Artificial neural networks in medical diagnosis. Int. J. Comput. Sci. Issues 8(2):150–154, 2011.
[3] Atanassov, K. T., Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20(1):87–96, 1986.
[4] Bauer, J., Spackman, S., Chiappelli, F., and Prolo, P., Model of evidence-based dental decision making. J. Evid. Based Dent. Pract. 5(4):189–197, 2005.
[5] Bedregal, I. A. D. S. B., and Bustince, H., Weighted average operators generated by n-dimensional overlaps and an application in decision making. Proceeding of 16th World Congress of the International Fuzzy Systems Association (IFSA) (pp. 1473–1478), 2015.
[6] Chattopadhyay, S., Davis, R. M., Menezes, D. D., Singh, G., Acharya, R. U., and Tamura, T., Application of Bayesian classifier for the diagnosis of dental pain. J. Med. Syst. 36(3):1425–1439, 2012.
[7] Cornelis, C., Victor, P., and Herrera-Viedma, E., Ordered weighted averaging approaches for aggregating gradual trust and distrust. XV Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF-2010) (pp. 555–560), 2010.
[8] Deepak, D., and John, S. J., Information systems on hesitant fuzzy sets. Int. J. Rough Sets Data Anal. 3(1):71–97, 2016.
[9] Farahbod, F., and Eftekhari, M., Comparison of different t-norm operators in classification problems. arXiv preprint arXiv:1208.1955, 2012.
[10] Fujita, H., Knowledge-based in medical decision support system based on subjective intelligence. J. Med. Inf. Technol. 22:13–19, 2013.
[11] Hossain, K. M., Raihan, Z., and Hashem, M. M. A., On appropriate selection of fuzzy aggregation operators in medical decision support system. arXiv preprint arXiv:1304.2538, 2013.
[12] Kavitha, M. S., Asano, A., Taguchi, A., Kurita, T., and Sanada, M., Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system. BMC Med. Imaging 12(1):1, 2012.
[13] Langland, O. E., Langlais, R. P., and Preece, J. W., Principles of dental imaging. Lippincott Williams & Wilkins, 2002.
[14] Lee, M. C., Chang, J. F., and Chen, J. F., Fuzzy preference relations in group decision making problems based on ordered weighted averaging operators. Int. J. Artif. Intell. Appl. Smart Devices 2(1):11–22, 2014.
[15] Said, E., Fahmy, G. F., Nassar, D., and Ammar, H., Dental x-ray image segmentation. In: Defense and Security (pp. 409–417). International Society for Optics and Photonics, 2004.
[16] Shouzhen, Z., Qifeng, W., Merigó, J. M., and Tiejun, P., Induced intuitionistic fuzzy ordered weighted averaging-weighted average operator and its application to business decision-making. Comput. Sci. Inf. Syst. 11(2):839–857, 2014.
[17] Son, L. H., and Tuan, T. M., A cooperative semi-supervised fuzzy clustering framework for dental X-ray image segmentation. Expert Syst. Appl. 46:380–393, 2016.
[18] Tuan, T.M., Duc, N.T., Hai, P.V., and Son, L.H., Dental diagnosis from X-Ray images using fuzzy rule-based systems. Int. J. Fuzzy Syst. Appl., in press, 2017.
[19] Tuan, T. M., Ngan, T. T., and Son, L. H., A novel semi-supervised fuzzy clustering method based on interactive fuzzy satisficing for dental X-ray image segmentation. Appl. Intell. 45(2):402–428, 2016.
[20] Tuan, T. M., and Son, L. H., A novel framework using graph-based clustering for dental x-ray image search in medical diagnosis. Int. J. Eng. Technol. 8(6):422–427, 2016.
[21] Tyagi, S., and Bharadwaj, K. K., A particle swarm optimization approach to fuzzy case-based reasoning in the framework of collaborative filtering. Int. J. Rough Sets Data Anal. 1(1):48–64, 2014.
[22] Wan, S. P., Wang, F., Lin, L. L., and Dong, J. Y., Some new generalized aggregation operators for triangular intuitionistic fuzzy numbers and application to multi-attribute group decision making. Comput. Ind. Eng. 93:286–301, 2016.