Abstract
Handling uncertainty in a medical diagnostic information system is a challenging and difficult problem. The recent Hesitant Fuzzy set has been introduced to control hesitant situations in which experts have hesitated about their opinion for rating a state of the system. Most of the diagnostics is discussed in a quantitative setting. But in some situations, it is difficult for rating quantitatively and calculation complexity is higher than the qualitative setting. In this article, to overcome such difficulty, we have used the Hesitant Fuzzy Linguistic Approach to design this diagnostic information system.
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
Similar content being viewed by others
References
Bonissone, P.P.: A fuzzy sets based linguistic approach: theory and applications. In: Approximate Reasoning in Decision Analysis, pp. 329–339 (1982)
Bordogna, G., Pasi, G.: A fuzzy linguistic approach generalizing boolean information retrieval: a model and its evaluation. J. Am. Soc. Inf. Sci. 44(2), 70–82 (1993)
Dong, Y., Xu, Y., Yu, S.: Computing the numerical scale of the linguistic term set for the 2-tuple fuzzy linguistic representation model. IEEE Trans. Fuzzy Syst. 17(6), 1366–1378 (2009)
Herrera, F., Alonso, S., Chiclana, F., Herrera-Viedma, E.: Computing with words in decision making: foundations, trends and prospects. Fuzzy Optim. Decis. Mak. 8(4), 337–364 (2009)
Mendel, J.M.: An architecture for making judgments using computing with words. Int. J. Appl. Math. Comput. Sci. 12, 325–335 (2002)
Orlovsky, S.: Decision-making with a fuzzy preference relation. Fuzzy Sets Syst. 1(3), 155–167 (1978)
Rodriguez, R.M., Martinez, L., Herrera, F.: Hesitant fuzzy linguistic term sets for decision making. IEEE Trans. Fuzzy Syst. 20(1), 109–119 (2012)
Sengupta, A., Pal, T.K.: On comparing interval numbers. Eur. J. Oper. Res. 127(1), 28–43 (2000)
Torra, V.: Hesitant fuzzy sets. Int. J. Intell. Syst. 25(6), 529–539 (2010)
Türkşen, I.B.: Type 2 representation and reasoning for CWW. Fuzzy Sets Syst. 127(1), 17–36 (2002)
Wang, J.H., Hao, J.: A new version of 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans. Fuzzy Syst. 14(3), 435–445 (2006)
Wang, Y.M., Yang, J.B., Xu, D.L.: A preference aggregation method through the estimation of utility intervals. Comput. Oper. Res. 32(8), 2027–2049 (2005)
Zadeh, L.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965). https://doi.org/10.1016/S0019-9958(65)90241-X
Zadeh, L.: Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. part 1 inform. sci. 8, 199–249; part 2. inform. sci. 8, 301-353; part 3. inform. sci. 9, 43-80 8, 199–249 (01 1975)
Zhou, S.M., John, R.I., Chiclana, F., Garibaldi, J.M.: On aggregating uncertain information by type-2 owa operators for soft decision making. Int. J. Intell. Syst. 25(6), 540–558 (2010)
Acknowledgements
The authors would like to sincerely thank the Medical Expert namely Dr. Ankon Mondal, General Physician for their kind suggestions and valuable observations for preparing the present research article.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Mondal, R., Verma, A., Gupta, P.K. (2020). A Medical Diagnostic Information System with Computing with Words Using Hesitant Fuzzy Sets. In: Dutta, D., Kar, H., Kumar, C., Bhadauria, V. (eds) Advances in VLSI, Communication, and Signal Processing. Lecture Notes in Electrical Engineering, vol 587. Springer, Singapore. https://doi.org/10.1007/978-981-32-9775-3_86
Download citation
DOI: https://doi.org/10.1007/978-981-32-9775-3_86
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-32-9774-6
Online ISBN: 978-981-32-9775-3
eBook Packages: EngineeringEngineering (R0)