Skip to main content
SpringerLink
Log in

A Novel TODIM Method-Based Three-Way Decision Model for Medical Treatment Selection

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

Three-way decision models and their relative applications have received a great deal of research attention. Most of these models were constructed on the basis of decision-theoretic rough sets (DTRSs) and Bayesian decision theory, both of which ignore the risk preferences of decision-makers. To address this shortcoming, this paper constructs a novel TODIM method-based three-way decision model and demonstrates its use in the context of online diagnosis and medical treatment selection. This model combines information systems and DTRSs together to construct a hybrid information system. And it solves the problems in aggregating cost-loss information with different levels of importance by utilizing the power average operator. Furthermore, an extension of the TODIM method is proposed based on the novel possibility degree measurement considering the probability distribution of loss functions. To validate the reasonableness and effectiveness of our model, we give a series of simulation experiments related to treatment selection for a Good Doctor Online user infected with the common cold.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Yao, Y.Y.: The superiority of three-way decisions in probabilistic rough set models. Inf. Sci. 181(6), 1080–1096 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  2. Liu, D., Yao, Y.Y., Li, T.R.: Three-way investment decisions with decision-theoretic rough sets. Int. J. Comput. Intell. Syst. 4(1), 66–74 (2011)

    Article  Google Scholar 

  3. Li, H.X., Zhou, X.Z.: Risk decision making based on decision-theoretic rough set: a three-way view decision model. Int. J. Comput. Intell. Syst. 4(1), 1–11 (2011)

    Article  MathSciNet  Google Scholar 

  4. Yao, Y.Y.: Three-way decision: an interpretation of rules in rough set theory. In: International Conference on Rough Sets and Knowledge Technology 2009, pp. 642–649

  5. Pawlak, Z.: Rough set theory and its applications to data analysis. Cybern. Syst. 29(7), 661–688 (1998)

    Article  MATH  Google Scholar 

  6. Yao, J.T., Azam, N.: Web-based medical decision support systems for three-way medical decision making with game-theoretic rough sets. IEEE Trans. Fuzzy Syst. 23(1), 3–15 (2015)

    Article  Google Scholar 

  7. Liu, D., Liang, D.C., Wang, C.C.: A novel three-way decision model based on incomplete information system. Knowl.-Based Syst. 91, 32–45 (2016)

    Article  Google Scholar 

  8. Yao, Y.Y.: An outline of a theory of three-way decisions. In: International Conference on Rough Sets and Current Trends in Computing 2012, pp. 1–17. Springer

  9. Yao, Y.Y., Zhou, B.: Naive Bayesian rough sets. In: International Conference on Rough Set and Knowledge Technology 2010, pp. 719–726

  10. Pawlak, Z.: Rough sets. Int. J. Comput. Inform. Sci. 11(5), 341–356 (1982)

    Article  MATH  Google Scholar 

  11. Ma, M.: Advances in three-way decisions and granular computing. Knowl.-Based Syst. 91, 1–3 (2016)

    Article  Google Scholar 

  12. Goudey, R.: Do statistical inferences allowing three alternative decisions give better feedback for environmentally precautionary decision-making? J. Environ. Manage. 85(2), 338–344 (2007)

    Article  Google Scholar 

  13. Peters, J.F., Ramanna, S.: Proximal three-way decisions: theory and applications in social networks. Knowl.-Based Syst. 91, 4–15 (2016)

    Article  Google Scholar 

  14. Jia, X.Y., Zheng, K., Li, W.W., Liu, T.T., Shang, L.: Three-way decisions solution to filter spam email: an empirical study. In: International Conference on Rough Sets and Current Trends in Computing 2012, pp. 287–296. Springer

  15. Zhou, B., Yao, Y.Y., Luo, J.G.: Cost-sensitive three-way email spam filtering. J. Intell. Inf. Syst. 42(1), 19–45 (2014)

    Article  Google Scholar 

  16. Liu, D., Li, T.R., Liang, D.C.: Three-way government decision analysis with decision-theoretic rough sets. Int. J. Uncertain. Fuzz. Knowl.-Based Syst. 20(01), 119–132 (2012)

    Article  Google Scholar 

  17. Zhang, H.R., Min, F.: Three-way recommender systems based on random forests. Knowl.-Based Syst. 91, 275–286 (2016)

    Article  Google Scholar 

  18. Zhang, H.R., Min, F., Shi, B.: Regression-based three-way recommendation. Inf. Sci. 378, 444–461 (2017)

    Article  Google Scholar 

  19. Hu, B.Q.: Three-way decision spaces based on partially ordered sets and three-way decisions based on hesitant fuzzy sets. Knowl.-Based Syst. 91, 16–31 (2016)

    Article  Google Scholar 

  20. Liang, D.C., Liu, D.: Deriving three-way decisions from intuitionistic fuzzy decision-theoretic rough sets. Inf. Sci. 300, 28–48 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  21. Sayadi, M.K., Heydari, M., Shahanaghi, K.: Extension of VIKOR method for decision making problem with interval numbers. Appl. Math. Model. 33(5), 2257–2262 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  22. Liu, J.S., Wang, X.Z., Zhang, B.Y.: The ranking of interval numbers. Chin. J. Eng. Math. 18(4), 103–109 (2001)

    MathSciNet  MATH  Google Scholar 

  23. Li, D., Gu, Y.: Method for ranking interval numbers based on possibility degree. J. Syst. Eng. 23(2), 243 (2008)

    Google Scholar 

  24. Xu, Z.S., Da, Q.L.: Possibility degree method for ranking interval numbers and its application. J. Syst. Eng. 18(1), 67–70 (2003)

    Google Scholar 

  25. Hu, J.H., Zhang, Y., Chen, X.H., Liu, Y.M.: Multi-criteria decision making method based on possibility degree of interval type-2 fuzzy number. Knowl.-Based Syst. 43, 21–29 (2013)

    Article  Google Scholar 

  26. Liang, D.C., Liu, D.: Systematic studies on three-way decisions with interval-valued decision-theoretic rough sets. Inf. Sci. 276, 186–203 (2014)

    Article  Google Scholar 

  27. Liang, D.C., Pedrycz, W., Liu, D., Hu, P.: Three-way decisions based on decision-theoretic rough sets under linguistic assessment with the aid of group decision making. Appl. Soft Comput. 29, 256–269 (2015)

    Article  Google Scholar 

  28. Yager, R.R.: The power average operator. IEEE Trans. Syst. Man Cybern.-A: Syst. Hum. 31(6), 724–731 (2001)

    Article  Google Scholar 

  29. Peng, H.G., Wang, J.Q.: Hesitant uncertain linguistic Z-numbers and their application in multi-criteria group decision-making problems. Int. J. Fuzzy Syst. 1–17 (2016). doi:10.1007/s40815-016-0257-y  

  30. Peng, J.J., Wang, J.Q., Wu, X.H., Tian, C.: Hesitant intuitionistic fuzzy aggregation operators based on the Archimedean t-norms and t-conorms. Int. J. Fuzzy Syst. 1–13 (2017). doi:10.1007/s40815-017-0303-4

  31. Wan, S.P.: Power average operators of trapezoidal intuitionistic fuzzy numbers and application to multi-attribute group decision making. Appl. Math. Model. 37(6), 4112–4126 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  32. Xu, Z.S., Cai, X.Q.: Uncertain power average operators for aggregating interval fuzzy preference relations. Group Decis. Negot. 21(3), 381–397 (2012)

    Article  Google Scholar 

  33. Peng, J.J., Wang, J.Q., Wu, X.H., Wang, J., Chen, X.H.: Multi-valued neutrosophic sets and power aggregation operators with their applications in multi-criteria group decision-making problems. Int. J. Comput. Intell. Syst. 8(2), 345–363 (2015)

    Article  Google Scholar 

  34. Zhang, Z.M.: Some hesitant multiplicative aggregation operators and their application in group decision making with hesitant multiplicative preference relations. Int. J. Fuzzy Syst. 18(2), 177–197 (2016)

    Article  MathSciNet  Google Scholar 

  35. Jiang, L., Liu, H.B., Cai, J.F.: The power average operator for unbalanced linguistic term sets. Inf. Fusion 22, 85–94 (2015)

    Article  Google Scholar 

  36. Yao, Y.Y.: Three-way decisions with probabilistic rough sets. Inf. Sci. 180(3), 341–353 (2010)

    Article  MathSciNet  Google Scholar 

  37. Yu, S.M., Wang, J., Wang, J.Q.: An extended TODIM approach with intuitionistic linguistic numbers. Int. Trans. Oper. Res. (2016). doi:10.1111/itor.12363

  38. Wang, J., Wang, J.Q., Zhang, H.Y.: A likelihood-based TODIM approach based on multi-hesitant fuzzy linguistic information for evaluation in logistics outsourcing. Comput. Ind. Eng. 99C, 287–299 (2016)

    Article  Google Scholar 

  39. Gomes, L., Lima, M.: From modeling individual preferences to multicriteria ranking of discrete alternatives: a look at Prospect Theory and the additive difference model. Found. Comput. Decis. Sci. 17(3), 171–184 (1992)

    MATH  Google Scholar 

  40. Gomes, L.F.A.M., Lima, M.M.P.P.: Todim: Basic and application to multicriteria ranking of projects with environmental impacts. Paris 16(4), 113–127 (1991)

    MATH  Google Scholar 

  41. Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econom.: J. Econom. Soc. 47(2), 263–291 (1979)

    Article  MATH  Google Scholar 

  42. Liu, P.D., Teng, F.: An extended TODIM method for multiple attribute group decision-making based on 2-dimension uncertain linguistic Variable. Complexity 21(5), 20–30 (2014)

    Article  MathSciNet  Google Scholar 

  43. Gomes, L.F.A.M., Rangel, L.S.A.D.: An application of the TODIM method to the multicriteria rental evaluation of residential properties. Eur. J. Oper. Res. 193(1), 204–211 (2009)

    Article  MATH  Google Scholar 

  44. Lourenzutti, R., Krohling, R.A.: A study of TODIM in a intuitionistic fuzzy and random environment. Expert Syst. Appl. 40(16), 6459–6468 (2013)

    Article  Google Scholar 

  45. Tseng, M.-L., Lin, Y.H., Tan, K., Chen, R.H., Chen, Y.H.: Using TODIM to evaluate green supply chain practices under uncertainty. Appl. Math. Model. 38(11), 2983–2995 (2014)

    Article  MathSciNet  Google Scholar 

  46. Ji, P., Zhang, H.Y., Wang, J.Q.: A projection-based TODIM method under multi-valued neutrosophic environments and its application in personnel selection. Neural Comput. Appl. (2016). doi:10.1007/s00521-016-2436-z

    Google Scholar 

  47. Whitehead, J., Brunier, H.: Bayesian decision procedures for dose determining experiments. Stat. Med. 14(9), 885–893 (1995)

    Article  Google Scholar 

  48. Gomes, L., Lima, M.: TODIM: Basics and application to multicriteria ranking of projects with environmental impacts. Found. Comput. Decis. Sci. 16(4), 113–127 (1992)

    MATH  Google Scholar 

  49. Jiang, Y.P., Liang, X., Liang, H.M.: An I-TODIM method for multi-attribute decision making with interval numbers. Soft Comput. 1–18 (2016). doi:10.1007/s00500-016-2139-5

  50. Nehi, H.M.: A new ranking method for intuitionistic fuzzy numbers. Int. J. Fuzzy Syst. 12(1), 80–86 (2010)

    MathSciNet  Google Scholar 

  51. Sun, H.L., Yao, W.X.: Comments on methods for ranking interval numbers. J. Syst. Eng. 3, 005 (2010)

    Google Scholar 

  52. Xu, Z.S., Da, Q.L.: The uncertain OWA operator. Int. J. Intell. Syst. 17(6), 569–575 (2002)

    Article  MATH  Google Scholar 

  53. Qian, W.Y., Zeng, Z.: Method for ranking interval rough numbers based on possibility degree. Oper. Res. Manage. Sci. 22(1), 71–76 (2013)

    Google Scholar 

  54. Gao, F.J.: Possibility degree and comprehensive priority of interval numbers. Syst. Eng.-Theory Pract. 33(8), 2033–2040 (2013)

    Google Scholar 

  55. Tao, Z.F., Liu, X., Chen, H.Y., Zhou, L.G.: Ranking interval-valued fuzzy numbers with intuitionistic fuzzy possibility degree and its application to fuzzy multi-attribute decision making. Int. J. Fuzzy Syst. 1–13 (2016). doi:10.1007/s40815-016-0193-x

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 71371196 and 71210003).

Author information

Authors and Affiliations

  1. School of Business, Central South University, Changsha, 410083, China

    Junhua Hu, Yao Yang & Xiaohong Chen

Authors
  1. Junhua Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yao Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaohong Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Junhua Hu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, J., Yang, Y. & Chen, X. A Novel TODIM Method-Based Three-Way Decision Model for Medical Treatment Selection. Int. J. Fuzzy Syst. 20, 1240–1255 (2018). https://doi.org/10.1007/s40815-017-0320-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-017-0320-3

Keywords

Search

Navigation