Abstract
Traditional fuzzy set theory has recently demonstrated its inefficiency in handling linguistic terms directly, including the degree of neutrality in medical diagnoses. Most decision support systems in medical diagnoses are restricted since both explicit and tacit knowledge of doctors involving linguistic semantics while making decisions have not been considered in the system. Thus this paper has presented a novel approach utilizing hedge algebra and picture fuzzy sets applying for a medical decision support system. In the proposed model, picture fuzzy rule-based approach and hedge algebra using linguistic semantics are used to express rules and preferences which aims to support doctors in diagnosing patients. Experimental results in simulations for the proposed method demonstrate a high level of precision and confidence, indicating its potential utilization in medical diagnostic domain.
Similar content being viewed by others
Change history
08 July 2023
City, country names were published incorrectly in the affiliation 2 and corrected in this version.
References
Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)
Moore, P., Pham, H.V.: On context and the open world assumption. In: 2015 IEEE 29th international conference on advanced information networking and applications workshops, pp. 387–392. (2015).https://doi.org/10.1109/WAINA.2015.7
Atanassov, K.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20(1), 87–96 (1986)
Atanassov, K.T.: New topological operator over intuitionistic fuzzy sets. J. Comput. Cogn. Eng. 1(3), 94–102 (2022). https://doi.org/10.47852/bonviewJCCE2202197
Cuong, B.: Picture fuzzy sets. J. Comput. Sci. Cybern. (2015). https://doi.org/10.15625/1813-9663/30/4/5032
Nguyen, C.H., Tran, D.K., Van Nam, H., Nguyen, H.C.: Hedge algebras, linguistic-valued logic and their application to fuzzy reasoning. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 7, 347–361 (1999). https://doi.org/10.1142/S0218488599000301
Ho, N.C., Wechler, W.: Hedge algebras: an algebraic approach to structures of sets of linguistic domains of linguistic truth variables. Fuzzy Sets Syst. 35, 281–293 (1990)
Ho, N.C., Nhu Lan, V., Xuan Viet, L.: Optimal hedge-algebras based controller: design and application. Fuzzy Sets Syst. 159, 968–989 (2008)
Nguyen, C.H., Nhu, V., Le Xuan, V.: An interpolative reasoning method based on hedge algebras and its application to a problem of fuzzy control. In: Proceedings of the 10th WSEAS international on computers, Vouliagmeni, Athens, Greece, July, pp. 526–534 (2006)
Kim, L.C., Pham, H.V.: An integrated picture fuzzy set with TOPSIS-AHP approach to group decision-making in policymaking under uncertainty. Int. J. Math. Eng. Manag. Sci. 6(6), 1578–1593 (2021). https://doi.org/10.33889/IJMEMS.2021.6.6.094
Shah, J.A., Sukheja, D., Bhatnagar, P., Jain, A.: A decision-making problem using dissimilarity measure in picture fuzzy sets. Mater. Today (2021). https://doi.org/10.1016/j.matpr.2021.07.261
Luo, M., Zhang, Y., Fu, L.: A new similarity measure for picture fuzzy sets and its application to multi-attribute decision making. Informatica 32, 1–22 (2021). https://doi.org/10.15388/21-INFOR452
Phong, P.H., Hieu, D.T., Ngan, R.T., Them, P.T.: Some compositions of picture fuzzy relations (2014)
Lan, L.T.H., et al.: A new complex fuzzy inference system with fuzzy knowledge graph and extensions in decision making. IEEE Access 8, 164899–164921 (2020). https://doi.org/10.1109/ACCESS.2020.3021097
Son, L.H., et al.: Predictive reliability and validity of hospital cost analysis with dynamic neural network and genetic algorithm. Neural Comput. Appl. 32, 15237–15248 (2020). https://doi.org/10.1007/s00521-020-04876-w
Long, C.K., Van Hai, P., Tuan, T.M., et al.: A novel fuzzy knowledge graph pairs approach in decision making. Multimed. Tools Appl. 81, 26505–26534 (2022). https://doi.org/10.1007/s11042-022-13067-9
VanPham, H., Khoa, N.D., Bui, T.T., Giang, N.T., Moore, P.: Applied picture fuzzy sets for group decision-support in the evaluation of pedagogic systems. Int. J. Math. Eng. Manag. Sci. 7(2), 243–257 (2022). https://doi.org/10.33889/IJMEMS.2022.7.2.016
Pham, H.V., Nguyen, Q.H.: The Clustering Approach Using SOM and Picture Fuzzy Sets for Tracking Influenced COVID-19 Persons. Artificial Intelligence in Data and Big Data Processing. ICABDE 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 124. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-97610-1_42
Zhao, X.K., Zhu, X.M., Bai, K.Y., Zhang, R.T.: A novel failure mode and effect analysis method using a flexible knowledge acquisition framework based on picture fuzzy sets. Eng. Appl. Artif. Intell. 117, 105625 (2023). https://doi.org/10.1016/j.engappai.2022.105625
Pham, V.H., et al.: The proposed context matching algorithm and its application for user preferences of tourism in COVID-19 pandemic. In: International conference on innovative computing and communications. lecture notes in networks and systems, vol. 471. Springer, Singapore (2023). https://doi.org/10.1007/978-981-19-2535-1_22
Juan, J.P., et al.: Picture fuzzy large-scale group decision-making in a trust- relationship-based social network environment. Inf. Sci. 608, 1675–1701 (2022). https://doi.org/10.1016/j.ins.2022.07.019
Akram, M., Ullah, I., Allahviranloo, T.: A new method to solve linear programming problems in the environment of picture fuzzy sets. Iran. J. Fuzzy Syst. 1, 1 (2022). https://doi.org/10.22111/IJFS.2022.7117
Kumar, S., Garg, H.: Some novel point operators and multiple rounds voting process based decision-making algorithm under picture fuzzy set environment. Adv. Eng. Softw. 174, 103274 (2022). https://doi.org/10.1016/j.advengsoft.2022.103274
Garg, H., et al.: Algorithm for multi-attribute decision-making using T-spherical fuzzy Maclaur in symmetric mean operator. Iran. J. Fuzzy Syst. 19(6), 111–124 (2022)
Ngoc, V.T.N., et al.: VNU-diagnosis: a novel medical system based on deep learning for diagnosis of periapical inflammation from X-rays images. J. Intell. Fuzzy Syst. 43(1), 1417–1427 (2022)
Ünver, M., Olgun, M., Türkarslan, E.: Cosine and cotangent similarity measures based on Choquet integral for spherical fuzzy sets and applications to pattern recognition. J. Comput. Cogn. Eng. 1(1), 21–31 (2022). https://doi.org/10.47852/bonviewJCCE2022010105
Si, A., Das, S., Kar, S.: Picture fuzzy set-based decision-making approach using Dempster–Shafer theory of evidence and grey relation analysis and its application in COVID-19 medicine selection. Soft Comput. (2021). https://doi.org/10.1007/s00500-021-05909-9
Khan, W., Faiz, K., Taouti, A.: Bipolar picture fuzzy sets and relations with applications. Songklanakarin J. Sci. Technol. 44, 987–999 (2022)
Verma, R., Rohtagi, B.: Novel similarity measures between picture fuzzy sets and their applications to pattern recognition and medical diagnosis. Granul. Comput. 7, 1–17 (2022). https://doi.org/10.1007/s41066-021-00294-y
Van Pham, H., Moore, P., Cuong, B.C.: Applied picture fuzzy sets with knowledge reasoning and linguistics in clinical decision support system. Neurosci. Inf. (2022). https://doi.org/10.1016/j.neuri.2022.100109
Nguyen, C.H., Tran, K., Huynh, V.-N., Nguyen, C.: Hedge algebras, linguistic-valued logic and their application to fuzzy reasoning. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 7, 347–361 (1999). https://doi.org/10.1142/S0218488599000301
Ho, N.C., Nam, H.V.: An algebraic approach to linguistic hedges in Zadeh’s fuzzy logic. Fuzzy Sets Syst. 129, 229–254 (2002)
Nguyen, C.H., Long, T.N.: Fuzziness measure on complete hedge algebras and quantifying semantics of terms in linear hedge algebras. Fuzzy Sets Syst. 158, 452–471 (2007)
Cuong, B.C.: Picture Fuzzy Sets First Results. Part 1. Seminar Neuro-Fuzzy Systems with Applications. Institute of Mathematics, Hanoi (2013)
Cuong, B.C.: Picture Fuzzy Sets First Results. Part 2, Seminar Neuro-Fuzzy Systems with Applications. Institute of Mathematics, Hanoi (2013)
Cuong, B.C.: Picture fuzzy sets-a new concept for computational intelligence problems. In: Proceedings of the third world congress on information and communication technologies WICT’2013, Hanoi, Vietnam, December 15–18, pp. 1–6 (2013)
Acknowledgements
This research is funded by University of Economics Ho Chi Minh City, Vietnam (UEH).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Pham, H.V., Hoang, T.L., Hung, N.Q. et al. Proposed Intelligent Decision Support System Using Hedge Algebra Integrated with Picture Fuzzy Relations for Improvement of Decision-Making in Medical Diagnoses. Int. J. Fuzzy Syst. 25, 3260–3270 (2023). https://doi.org/10.1007/s40815-023-01548-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40815-023-01548-4