Zhou W, Liu X, Bai H, He L. Intelligent medical diagnosis and treatment for diabetes with deep convolutional fuzzy neural networks. Inf Sci. 2024;677:120802. https://doi.org/10.1016/j.ins.2024.120802.

Article  Google Scholar 

Zhang T, Xue G. Fuzzy attention-based deep neural networks for acute lymphoblastic leukemia diagnosis. Appl Soft Comput. 2025;171:112810. https://doi.org/10.1016/j.asoc.2025.112810.

Article  Google Scholar 

Vyas S, Gupta S, Bhargava D, Boddu R. Fuzzy logic system implementation on the performance parameters of health data management frameworks. J Healthc Eng. 2022;2022:9382322.

Article  Google Scholar 

Dehghani Saryazdi M, Mostafaeipour A. Identification and validation of key predictive factors for heart attack diagnosis using machine learning and fuzzy clustering. Eng Appl Artif Intell. 2025;142:109968. https://doi.org/10.1016/j.engappai.2024.109968.

Article  Google Scholar 

Khushal R, Fatima U. Fuzzy quantum machine learning logic for optimized disease prediction. Comput Biol Med. 2025;192:110315. https://doi.org/10.1016/j.compbiomed.2025.110315.

Article  Google Scholar 

Zadeh LA. Fuzzy sets. Inf Control. 1965;8:338–53. https://doi.org/10.1016/S0019-9958(65)90241-X.

Article  Google Scholar 

Nanehkaran YA, et al. Anomaly detection in heart disease using a density-based unsupervised approach. Wirel Commun Mob Comput. 2022;2022:6913043.

Article  Google Scholar 

Liu Q, Hu W, Yang K, Yang J. Risk assessment of urban underground logistics system operations in built-up areas using a hybrid fuzzy Bayesian network and machine learning approach. Comput Ind Eng. 2025;207:111295. https://doi.org/10.1016/j.cie.2025.111295.

Article  Google Scholar 

Jayalakshmi M, et al. Fuzzy logic-based health monitoring system for COVID-19 patients. Comput Mater Contin. 2021;67:2431–47.

Google Scholar 

Reddy GT, Reddy MPK, Lakshmanna K, Rajput DS, Kaluri R, Srivastava G. Hybrid genetic algorithm and fuzzy logic classifier for heart disease diagnosis. Evol Intell. 2020;13:185–96. https://doi.org/10.1007/s12065-019-00327-1.

Article  Google Scholar 

Lohani QMD, Solanki R, Muhuri PK. A convergence theorem and an experimental study of intuitionistic fuzzy c-mean algorithm over machine learning dataset. Appl Soft Comput. 2018;71:1176–88. https://doi.org/10.1016/j.asoc.2018.04.014.

Article  Google Scholar 

Atanassov KT. Intuitionistic fuzzy sets. Fuzzy Sets Syst. 1986;20:87–96. https://doi.org/10.1016/S0165-0114(86)80034-3.

Article  Google Scholar 

Khan VA, Yadav AK, Arshad M, Akhtar N. Lung cancer prediction using an enhanced neutrosophic set combined with a machine learning approach. Neutrosophic Sets Syst. 2025;88:1.

Google Scholar 

Zhou T, Wang H, Geng S, Ju H, Huang J, Fu F, et al. F2CAU-Net: a dual fuzzy medical image segmentation cascade method based on fuzzy feature learning. Appl Soft Comput. 2025;184:113692. https://doi.org/10.1016/j.asoc.2025.113692.

Article  Google Scholar 

Bai L, Chen X, Wang Z, Shao Y-H. Safe intuitionistic fuzzy twin support vector machine for semi-supervised learning. Appl Soft Comput. 2022;123:108906. https://doi.org/10.1016/j.asoc.2022.108906.

Article  Google Scholar 

Riaz M, Hashmi MR. Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems. J Intell Fuzzy Syst. 2019;37:5417–39.

Google Scholar 

Kannan J, Jayakumar V, Saeed M, Alballa T, Khalifa HAE-W, Gomaa HG. Linear Diophantine fuzzy clustering algorithm based on correlation coefficient with application to logistic efficiency. IEEE Access. 2024. https://doi.org/10.1109/ACCESS.2024.3371986.

Article  Google Scholar 

Jayakumar V, Kannan J, Kausar N, Deveci M, Wen X. Multicriteria group decision making for prioritizing IoT risk factors using linear Diophantine fuzzy sets and MARCOS method. Granul Comput. 2024;9:56. https://doi.org/10.1007/s41066-024-00480-8.

Article  Google Scholar 

Kannan J, Jayakumar V, Kausar N, Pamucar D, Simic V. Enhancing decision-making with linear Diophantine multi-fuzzy set using novel information measures. Sci Rep. 2024;14:79725. https://doi.org/10.1038/s41598-024-79725-0.

Article  Google Scholar 

Vimala J, Garg H, Jeevitha K. Prognostication of myocardial infarction using lattice ordered linear Diophantine multi-fuzzy soft set. Int J Fuzzy Syst. 2024;26:44–59. https://doi.org/10.1007/s40815-023-01574-2.

Article  Google Scholar 

Nazirkhan F. Heart disease prediction dataset. Kaggle Dataset (2024). https://www.kaggle.com/datasets/mfarhaannazirkhan/heart-dataset.