{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T21:22:50Z","timestamp":1773091370420,"version":"3.50.1"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s40747-025-02089-z","type":"journal-article","created":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T08:50:47Z","timestamp":1761295847000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Novel distance measures-based decision-making algorithm in Fermatean fuzzy environments: applications to pattern recognition and medical diagnosis"],"prefix":"10.1007","volume":"11","author":[{"given":"Jianping","family":"Fan","sequence":"first","affiliation":[]},{"given":"Zhuoyang","family":"He","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6126-1122","authenticated-orcid":false,"given":"Meiqin","family":"Wu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,24]]},"reference":[{"issue":"11","key":"2089_CR1","doi-asserted-by":"crossref","first-page":"14345","DOI":"10.1007\/s10489-022-04244-2","volume":"53","author":"G I\u015f\u0131k","year":"2023","unstructured":"I\u015f\u0131k G (2023) A framework for choosing an appropriate fuzzy set extension in modeling. Appl Intell 53(11):14345\u201314370","journal-title":"Appl Intell"},{"issue":"7","key":"2089_CR2","doi-asserted-by":"crossref","first-page":"6855","DOI":"10.1007\/s10462-022-10346-7","volume":"56","author":"TM Al-Shami","year":"2023","unstructured":"Al-Shami TM, Alshammari I (2023) Rough sets models inspired by supra-topology structures. Artif Intell Rev 56(7):6855\u20136883","journal-title":"Artif Intell Rev"},{"key":"2089_CR3","doi-asserted-by":"crossref","first-page":"104777","DOI":"10.1016\/j.engappai.2022.104777","volume":"111","author":"Q Zhao","year":"2022","unstructured":"Zhao Q, Ju Y, Dong P, Gonzalez EDS (2022) A hybrid decision making aided framework for multi-criteria decision making with r-numbers and preference models. Eng Appl Artif Intell 111:104777","journal-title":"Eng Appl Artif Intell"},{"key":"2089_CR4","doi-asserted-by":"crossref","first-page":"106104","DOI":"10.1016\/j.engappai.2023.106104","volume":"122","author":"S Maleki","year":"2023","unstructured":"Maleki S, Nourani V, Najafi H, Baghanam AH, Ke C-Q (2023) Z-numbers based novel method for assessing groundwater specific vulnerability. Eng Appl Artif Intell 122:106104","journal-title":"Eng Appl Artif Intell"},{"key":"2089_CR5","doi-asserted-by":"crossref","unstructured":"Liu Z, Letchmunan S (2024) Representing uncertainty and imprecision in machine learning: a survey on belief functions. J King Saud Univ Comput Inf Sci 36(1): 101904","DOI":"10.1016\/j.jksuci.2023.101904"},{"issue":"12","key":"2089_CR6","doi-asserted-by":"crossref","first-page":"15495","DOI":"10.1007\/s10462-023-10533-0","volume":"56","author":"Z Liu","year":"2023","unstructured":"Liu Z (2023) An effective conflict management method based on belief similarity measure and entropy for multi-sensor data fusion. Artif Intell Rev 56(12):15495\u201315522","journal-title":"Artif Intell Rev"},{"key":"2089_CR7","doi-asserted-by":"crossref","first-page":"103490","DOI":"10.1016\/j.autcon.2020.103490","volume":"122","author":"S-S Lin","year":"2021","unstructured":"Lin S-S, Shen S-L, Zhou A, Xu Y-S (2021) Risk assessment and management of excavation system based on fuzzy set theory and machine learning methods. Autom Constr 122:103490","journal-title":"Autom Constr"},{"issue":"3","key":"2089_CR8","first-page":"338","volume":"8","author":"LA Zadeh","year":"1965","unstructured":"Zadeh LA (1965) Information and control. Fuzzy Sets 8(3):338\u2013353","journal-title":"Fuzzy Sets"},{"key":"2089_CR9","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-7908-1870-3","volume-title":"Intuitionistic fuzzy sets","author":"KT Atanassov","year":"1999","unstructured":"Atanassov KT, Atanassov KT (1999) Intuitionistic fuzzy sets. Springer, Berlin"},{"issue":"4","key":"2089_CR10","doi-asserted-by":"crossref","first-page":"2068","DOI":"10.1007\/s40815-021-01247-y","volume":"24","author":"H Hashim","year":"2022","unstructured":"Hashim H, Garg H, Al-Quran A, Awang NA, Abdullah L (2022) Heronian mean operators considering Shapley fuzzy measure under interval neutrosophic vague environment for an investment decision. Int J Fuzzy Syst 24(4):2068\u20132091","journal-title":"Int J Fuzzy Syst"},{"key":"2089_CR11","doi-asserted-by":"crossref","unstructured":"Hussain A, Latif S, Ullah K, Garg H, Al-Quran A (2024) Pythagorean fuzzy aczel alsina hamy mean aggregation operators and its applications to multi-attribute decision-making process. J Intell Fuzzy Syst 46(2):3141\u20133171","DOI":"10.3233\/JIFS-232691"},{"issue":"1","key":"2089_CR12","first-page":"189","volume":"36","author":"NX Thao","year":"2019","unstructured":"Thao NX, Ali M, Smarandache F (2019) An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis. J Intell Fuzzy Syst 36(1):189\u2013198","journal-title":"J Intell Fuzzy Syst"},{"key":"2089_CR13","doi-asserted-by":"crossref","first-page":"107878","DOI":"10.1016\/j.engappai.2024.107878","volume":"132","author":"Z Liu","year":"2024","unstructured":"Liu Z (2024) Fermatean fuzzy similarity measures based on Tanimoto and S\u00f8rensen coefficients with applications to pattern classification, medical diagnosis and clustering analysis. Eng Appl Artif Intell 132:107878","journal-title":"Eng Appl Artif Intell"},{"issue":"2","key":"2089_CR14","first-page":"731","volume":"29","author":"Z Su","year":"2015","unstructured":"Su Z, Xu Z, Liu H, Liu S (2015) Distance and similarity measures for dual hesitant fuzzy sets and their applications in pattern recognition. J Intell Fuzzy Syst 29(2):731\u2013745","journal-title":"J Intell Fuzzy Syst"},{"key":"2089_CR15","doi-asserted-by":"crossref","first-page":"118908","DOI":"10.1016\/j.eswa.2022.118908","volume":"213","author":"W Wang","year":"2023","unstructured":"Wang W, Lin W, Wen Y, Lai X, Peng P, Zhang Y, Li K (2023) An interpretable intuitionistic fuzzy inference model for stock prediction. Expert Syst Appl 213:118908","journal-title":"Expert Syst Appl"},{"issue":"20","key":"2089_CR16","doi-asserted-by":"crossref","first-page":"15133","DOI":"10.1007\/s00500-023-08336-0","volume":"27","author":"C Wu","year":"2023","unstructured":"Wu C, Zou H, Barnes D (2023) A supply risk perspective integrated sustainable supplier selection model in the intuitionistic fuzzy environment. Soft Comput 27(20):15133\u201315151","journal-title":"Soft Comput"},{"issue":"4","key":"2089_CR17","doi-asserted-by":"crossref","first-page":"3543","DOI":"10.1007\/s10462-022-10251-z","volume":"56","author":"P Dutta","year":"2023","unstructured":"Dutta P, Borah G (2023) Multicriteria group decision making via generalized trapezoidal intuitionistic fuzzy number-based novel similarity measure and its application to diverse covid-19 scenarios. Artif Intell Rev 56(4):3543\u20133617","journal-title":"Artif Intell Rev"},{"issue":"4","key":"2089_CR18","doi-asserted-by":"crossref","first-page":"958","DOI":"10.1109\/TFUZZ.2013.2278989","volume":"22","author":"RR Yager","year":"2013","unstructured":"Yager RR (2013) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22(4):958\u2013965","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"2089_CR19","doi-asserted-by":"crossref","first-page":"106084","DOI":"10.1016\/j.engappai.2023.106084","volume":"121","author":"W Ren","year":"2023","unstructured":"Ren W, Du Y, Sun R, Du Y (2023) Development of feature extraction method based on interval-valued pythagorean fuzzy decision theory. Eng Appl Artif Intell 121:106084","journal-title":"Eng Appl Artif Intell"},{"key":"2089_CR20","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.ins.2022.12.064","volume":"624","author":"K Kumar","year":"2023","unstructured":"Kumar K, Chen S-M (2023) Group decision making based on entropy measure of pythagorean fuzzy sets and pythagorean fuzzy weighted arithmetic mean aggregation operator of pythagorean fuzzy numbers. Inf Sci 624:361\u2013377","journal-title":"Inf Sci"},{"key":"2089_CR21","doi-asserted-by":"crossref","first-page":"106089","DOI":"10.1016\/j.engappai.2023.106089","volume":"122","author":"SM Khalil","year":"2023","unstructured":"Khalil SM, Sharqi MS (2023) Some applications in decision-making using cosine maps and the relevance of the pythagorean fuzzy. Eng Appl Artif Intell 122:106089","journal-title":"Eng Appl Artif Intell"},{"key":"2089_CR22","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1007\/s12652-019-01377-0","volume":"11","author":"T Senapati","year":"2020","unstructured":"Senapati T, Yager RR (2020) Fermatean fuzzy sets. J Ambient Intell Humaniz Comput 11:663\u2013674","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"2089_CR23","doi-asserted-by":"crossref","first-page":"106603","DOI":"10.1016\/j.engappai.2023.106603","volume":"124","author":"AR Mishra","year":"2023","unstructured":"Mishra AR, Rani P, Deveci M, Gokasar I, Pamucar D, Govindan K (2023) Interval-valued Fermatean fuzzy Heronian mean operator-based decision-making method for urban climate change policy for transportation activities. Eng Appl Artif Intell 124:106603","journal-title":"Eng Appl Artif Intell"},{"key":"2089_CR24","doi-asserted-by":"crossref","first-page":"106385","DOI":"10.1016\/j.engappai.2023.106385","volume":"123","author":"Y Pan","year":"2023","unstructured":"Pan Y, Zeng S, Chen W, Gu J (2023) Service quality evaluation of crowdsourcing logistics platform based on Fermatean fuzzy Todim and regret theory. Eng Appl Artif Intell 123:106385","journal-title":"Eng Appl Artif Intell"},{"key":"2089_CR25","doi-asserted-by":"crossref","first-page":"118497","DOI":"10.1016\/j.eswa.2022.118497","volume":"211","author":"A Saha","year":"2023","unstructured":"Saha A, Pamucar D, Gorcun OF, Mishra AR (2023) Warehouse site selection for the automotive industry using a Fermatean fuzzy-based decision-making approach. Expert Syst Appl 211:118497","journal-title":"Expert Syst Appl"},{"key":"2089_CR26","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.engappai.2019.05.012","volume":"85","author":"T Senapati","year":"2019","unstructured":"Senapati T, Yager RR (2019) Fermatean fuzzy weighted averaging\/geometric operators and its application in multi-criteria decision-making methods. Eng Appl Artif Intell 85:112\u2013121","journal-title":"Eng Appl Artif Intell"},{"issue":"22","key":"2089_CR27","doi-asserted-by":"crossref","first-page":"13869","DOI":"10.1007\/s00500-021-06252-9","volume":"25","author":"C Shit","year":"2021","unstructured":"Shit C, Ghorai G (2021) Multiple attribute decision-making based on different types of Dombi aggregation operators under Fermatean fuzzy information. Soft Comput 25(22):13869\u201313880","journal-title":"Soft Comput"},{"key":"2089_CR28","doi-asserted-by":"crossref","first-page":"111427","DOI":"10.1016\/j.asoc.2024.111427","volume":"155","author":"S Memarian","year":"2024","unstructured":"Memarian S, Behmanesh-Fard N, Aryai P, Shokouhifar M, Mirjalili S, Carmen Romero-Ternero M (2024) Tsfis-gwo: metaheuristic-driven Takagi\u2013Sugeno fuzzy system for adaptive real-time routing in wbans. Appl Soft Comput 155:111427","journal-title":"Appl Soft Comput"},{"key":"2089_CR29","doi-asserted-by":"crossref","first-page":"102669","DOI":"10.1016\/j.scs.2020.102669","volume":"66","author":"M Zivkovic","year":"2021","unstructured":"Zivkovic M, Bacanin N, Venkatachalam K, Nayyar A, Djordjevic A, Strumberger I, Al-Turjman F (2021) Covid-19 cases prediction by using hybrid machine learning and beetle antennae search approach. Sustain Cities Soc 66:102669","journal-title":"Sustain Cities Soc"},{"issue":"3","key":"2089_CR30","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1134\/S1054661824700809","volume":"34","author":"M Bardamova","year":"2024","unstructured":"Bardamova M, Svetlakov M, Sarin K, Hodashinskaya A, Shurygin Y, Hodashinsky I (2024) Population generation methods for metaheuristic algorithms used to construct compact fuzzy classifiers of medical data. Pattern Recognit Image Anal 34(3):396\u2013411","journal-title":"Pattern Recognit Image Anal"},{"issue":"3","key":"2089_CR31","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1016\/S0165-0114(98)00244-9","volume":"114","author":"E Szmidt","year":"2000","unstructured":"Szmidt E, Kacprzyk J (2000) Distances between intuitionistic fuzzy sets. Fuzzy Sets Syst 114(3):505\u2013518","journal-title":"Fuzzy Sets Syst"},{"issue":"13","key":"2089_CR32","doi-asserted-by":"crossref","first-page":"2063","DOI":"10.1016\/j.patrec.2005.03.018","volume":"26","author":"W Wang","year":"2005","unstructured":"Wang W, Xin X (2005) Distance measure between intuitionistic fuzzy sets. Pattern Recogn Lett 26(13):2063\u20132069","journal-title":"Pattern Recogn Lett"},{"key":"2089_CR33","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.knosys.2015.06.011","volume":"86","author":"Y Song","year":"2015","unstructured":"Song Y, Wang X, Zhang H (2015) A distance measure between intuitionistic fuzzy belief functions. Knowl Based Syst 86:288\u2013298","journal-title":"Knowl Based Syst"},{"key":"2089_CR34","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.artmed.2018.05.002","volume":"89","author":"M Luo","year":"2018","unstructured":"Luo M, Zhao R (2018) A distance measure between intuitionistic fuzzy sets and its application in medical diagnosis. Artif Intell Med 89:34\u201339","journal-title":"Artif Intell Med"},{"issue":"2","key":"2089_CR35","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1002\/int.22312","volume":"36","author":"J Mahanta","year":"2021","unstructured":"Mahanta J, Panda S (2021) A novel distance measure for intuitionistic fuzzy sets with diverse applications. Int J Intell Syst 36(2):615\u2013627","journal-title":"Int J Intell Syst"},{"issue":"12","key":"2089_CR36","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1002\/int.21676","volume":"29","author":"X Zhang","year":"2014","unstructured":"Zhang X, Xu Z (2014) Extension of topsis to multiple criteria decision making with pythagorean fuzzy sets. Int J Intell Syst 29(12):1061\u20131078","journal-title":"Int J Intell Syst"},{"issue":"11","key":"2089_CR37","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1002\/int.21896","volume":"32","author":"X Peng","year":"2017","unstructured":"Peng X, Dai J (2017) Approaches to pythagorean fuzzy stochastic multi-criteria decision making based on prospect theory and regret theory with new distance measure and score function. Int J Intell Syst 32(11):1187\u20131214","journal-title":"Int J Intell Syst"},{"issue":"2","key":"2089_CR38","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1002\/int.21934","volume":"33","author":"D Li","year":"2018","unstructured":"Li D, Zeng W (2018) Distance measure of pythagorean fuzzy sets. Int J Intell Syst 33(2):348\u2013361","journal-title":"Int J Intell Syst"},{"issue":"2","key":"2089_CR39","first-page":"1781","volume":"37","author":"Z Li","year":"2019","unstructured":"Li Z, Lu M (2019) Some novel similarity and distance measures of pythagorean fuzzy sets and their applications. J Intell Fuzzy Syst 37(2):1781\u20131799","journal-title":"J Intell Fuzzy Syst"},{"key":"2089_CR40","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.inffus.2017.09.003","volume":"41","author":"T-Y Chen","year":"2018","unstructured":"Chen T-Y (2018) Remoteness index-based pythagorean fuzzy vikor methods with a generalized distance measure for multiple criteria decision analysis. Inf Fusion 41:129\u2013150","journal-title":"Inf Fusion"},{"issue":"10","key":"2089_CR41","doi-asserted-by":"crossref","first-page":"2633","DOI":"10.1002\/int.22169","volume":"34","author":"Z Hussian","year":"2019","unstructured":"Hussian Z, Yang M-S (2019) Distance and similarity measures of pythagorean fuzzy sets based on the hausdorff metric with application to fuzzy topsis. Int J Intell Syst 34(10):2633\u20132654","journal-title":"Int J Intell Syst"},{"issue":"14","key":"2089_CR42","doi-asserted-by":"crossref","first-page":"10083","DOI":"10.1007\/s00521-022-07679-3","volume":"35","author":"PA Ejegwa","year":"2023","unstructured":"Ejegwa PA, Feng Y, Tang S, Agbetayo JM, Dai X (2023) New pythagorean fuzzy-based distance operators and their applications in pattern classification and disease diagnostic analysis. Neural Comput Appl 35(14):10083\u201310095","journal-title":"Neural Comput Appl"},{"issue":"11","key":"2089_CR43","doi-asserted-by":"crossref","first-page":"2807","DOI":"10.1002\/int.22162","volume":"34","author":"D Liu","year":"2019","unstructured":"Liu D, Liu Y, Wang L (2019) Distance measure for fermatean fuzzy linguistic term sets based on linguistic scale function: an illustration of the todim and topsis methods. Int J Intell Syst 34(11):2807\u20132834","journal-title":"Int J Intell Syst"},{"key":"2089_CR44","doi-asserted-by":"crossref","unstructured":"Deng Z, Wang J (2022) New distance measure for fermatean fuzzy sets and its application. Int J Intell Syst 37(3):1903\u20131930","DOI":"10.1002\/int.22760"},{"key":"2089_CR45","doi-asserted-by":"crossref","first-page":"105048","DOI":"10.1016\/j.engappai.2022.105048","volume":"114","author":"S Yang","year":"2022","unstructured":"Yang S, Pan Y, Zeng S (2022) Decision making framework based fermatean fuzzy integrated weighted distance and topsis for green low-carbon port evaluation. Eng Appl Artif Intell 114:105048","journal-title":"Eng Appl Artif Intell"},{"issue":"8","key":"2089_CR46","doi-asserted-by":"crossref","first-page":"8591","DOI":"10.1007\/s10462-022-10387-y","volume":"56","author":"S Zeng","year":"2023","unstructured":"Zeng S, Gu J, Peng X (2023) Low-carbon cities comprehensive evaluation method based on fermatean fuzzy hybrid distance measure and topsis. Artif Intell Rev 56(8):8591\u20138607","journal-title":"Artif Intell Rev"},{"issue":"1","key":"2089_CR47","doi-asserted-by":"crossref","first-page":"167","DOI":"10.31181\/jopi21202415","volume":"2","author":"Z Liu","year":"2024","unstructured":"Liu Z (2024) A distance measure of Fermatean fuzzy sets based on triangular divergence and its application in medical diagnosis. J Oper Intell 2(1):167\u2013178","journal-title":"J Oper Intell"},{"key":"2089_CR48","doi-asserted-by":"crossref","unstructured":"Ganie AH, Gheith NEM, Al-Qudah Y, Ganie AH, Sharma SK, Aqlan AM, Khalaf MM (2024) An innovative Fermatean fuzzy distance metric with its application in classification and bidirectional approximate reasoning. IEEE Access 12: 4780\u20134791","DOI":"10.1109\/ACCESS.2023.3348780"},{"key":"2089_CR49","doi-asserted-by":"crossref","first-page":"107451","DOI":"10.1016\/j.engappai.2023.107451","volume":"127","author":"F Gao","year":"2024","unstructured":"Gao F, Han M, Wang S, Gao J (2024) A novel Fermatean fuzzy bwm-vikor based multi-criteria decision-making approach for selecting health care waste treatment technology. Eng Appl Artif Intell 127:107451","journal-title":"Eng Appl Artif Intell"},{"issue":"4","key":"2089_CR50","doi-asserted-by":"crossref","first-page":"979","DOI":"10.1007\/s41066-021-00309-8","volume":"7","author":"AH Ganie","year":"2022","unstructured":"Ganie AH (2022) Multicriteria decision-making based on distance measures and knowledge measures of Fermatean fuzzy sets. Granul Comput 7(4):979\u2013998","journal-title":"Granul Comput"},{"key":"2089_CR51","doi-asserted-by":"crossref","first-page":"121310","DOI":"10.1016\/j.ins.2024.121310","volume":"686","author":"Z Liu","year":"2025","unstructured":"Liu Z, Zhu S, Senapati T, Deveci M, Pamucar D, Yager RR (2025) New distance measures of complex Fermatean fuzzy sets with applications in decision making and clustering problems. Inf Sci 686:121310","journal-title":"Inf Sci"},{"issue":"1","key":"2089_CR52","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1109\/18.61115","volume":"37","author":"J Lin","year":"1991","unstructured":"Lin J (1991) Divergence measures based on the Shannon entropy. IEEE Trans Inf Theory 37(1):145\u2013151","journal-title":"IEEE Trans Inf Theory"},{"key":"2089_CR53","volume-title":"Information theory and reliable communication","author":"RG Gallager","year":"1968","unstructured":"Gallager RG (1968) Information theory and reliable communication. Springer, Berlin"},{"issue":"1","key":"2089_CR54","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1109\/TIT.1975.1055311","volume":"21","author":"G Toussaint","year":"1975","unstructured":"Toussaint G (1975) Sharper lower bounds for discrimination information in terms of variation (corresp.). IEEE Trans Inf Theory 21(1):99\u2013100","journal-title":"IEEE Trans Inf Theory"},{"key":"2089_CR55","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.asoc.2019.03.043","volume":"79","author":"F Xiao","year":"2019","unstructured":"Xiao F, Ding W (2019) Divergence measure of pythagorean fuzzy sets and its application in medical diagnosis. Appl Soft Comput 79:254\u2013267","journal-title":"Appl Soft Comput"},{"issue":"1","key":"2089_CR56","doi-asserted-by":"crossref","first-page":"41","DOI":"10.22457\/ijfma.v14n1a6","volume":"14","author":"AE Samuel","year":"2017","unstructured":"Samuel AE, Rajakumar S (2017) Intuitionistic fuzzy sets and its applications in medical diagnosis. Int J Fuzzy Math Arch 14(1):41\u201345","journal-title":"Int J Fuzzy Math Arch"}],"container-title":["Complex & Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-02089-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-025-02089-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-02089-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T03:03:04Z","timestamp":1763175784000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-025-02089-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,24]]},"references-count":56,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["2089"],"URL":"https:\/\/doi.org\/10.1007\/s40747-025-02089-z","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,24]]},"assertion":[{"value":"2 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 September 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 October 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"478"}}