Fuzzy Theory in Healthcare: A Survey, Classification, Issues, and Future Directions

Fuzzy Theory in Healthcare: A Survey, Classification, Issues, and Future Directions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Fuzzy Theory in Healthcare: A Survey, Classification, Issues, and Future Directions Zaid Al-Araji, Balqees Hasan, Sharifah Sakinah Syed Ahmad, Ali Mohsin Ahmed Al-Sabaawi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7652348/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background: Fuzzy Logic (FL) is increasingly used in medical domains as it provides a robust framework for dealing with the uncertainty and subjectivity often encountered in clinical environments. With the increasing complexity of medical data and the growing need for interpretable decision-making, fuzzy systems have been widely adopted across diverse healthcare domains. Objective: This paper contributes a broad and well-structured survey of fuzzy logic techniques applied in diverse healthcare scenarios. It categorises the literature based on application domains, methodologies, data sources, and implementation tools while identifying common challenges and proposing future research directions. Methodology: A Systematic Literature Review (SLR) was conducted using five major databases: IEEE Xplore, Scopus, ScienceDirect and Web of Science. Articles published between 2017 and 2025 were filtered through established eligibility criteria to ensure relevance.The selected studies were classified into six major healthcare categories: diagnosis, monitoring, treatment recommendation, risk prediction, supporting infrastructure, and review papers. Results: The review includes over 147 studies, revealing that diagnosis is the most frequently targeted application area, with fuzzy inference systems and hybrid models being the most commonly used techniques. While FL systems show strengths in interpretability and adaptability, many suffer from a lack of clinical validation, limited datasets, and scalability concerns in real-world deployment. Discussion: The findings suggest that although FL continues to offer significant value in modelling clinical uncertainty and facilitating explainable reasoning, the field remains fragmented. There is limited standardisation across implementations, and many studies lack real-time capability or integration with hospital systems. Furthermore, most models rely on expert-driven rule design rather than data-driven tuning, limiting their adaptability to evolving medical knowledge. Decision Support Systems Fuzzy Theory Healthcare Intelligent Healthcare Medical Diagnosis Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 18 Jan, 2026 Reviews received at journal 15 Jan, 2026 Reviewers agreed at journal 15 Jan, 2026 Reviews received at journal 28 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers invited by journal 07 Oct, 2025 Editor assigned by journal 23 Sep, 2025 Submission checks completed at journal 22 Sep, 2025 First submitted to journal 18 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7652348","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531269053,"identity":"90651b21-90db-4c20-a322-d12362ff1e97","order_by":0,"name":"Zaid Al-Araji","email":"","orcid":"","institution":"Ninevah University","correspondingAuthor":false,"prefix":"","firstName":"Zaid","middleName":"","lastName":"Al-Araji","suffix":""},{"id":531269054,"identity":"6b670669-ec8b-4fc5-81b3-5fecaa9f346f","order_by":1,"name":"Balqees Hasan","email":"","orcid":"","institution":"Ninevah University","correspondingAuthor":false,"prefix":"","firstName":"Balqees","middleName":"","lastName":"Hasan","suffix":""},{"id":531269055,"identity":"15447b46-e424-4b70-8486-213a23cc46bd","order_by":2,"name":"Sharifah Sakinah Syed Ahmad","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIie3PsQrCMBCA4StC6lB1cynaV4gUXHyZFiFZFBwdOgSETqKrvkUfIXCYqeCaQdCproLgKBZ0EaSNm0h+yHCQD+4AbLYfLBAEJIDsv+ZGPaHySUIgxuT5VcbCnLgqxlly4NlxsctgPopFN6eVJFgyiRtVTDNFmIacx8KfVBOQXKBHsCTeUDspGpD9uSR35FR1btq5mxBdLtZKMaLKI9oRBoTqIsLWCgdbxYY6UjxMfTarJMGahVfvhkEbsdCXZNRb++OserG3ovIRaNbc8iH39DWx2Wy2v+4BbXpQ6zZcVeUAAAAASUVORK5CYII=","orcid":"","institution":"Mustansiriyah University","correspondingAuthor":true,"prefix":"","firstName":"Sharifah","middleName":"Sakinah Syed","lastName":"Ahmad","suffix":""},{"id":531269056,"identity":"3ed1b4ef-07eb-4cfc-870f-d9500eb80fa1","order_by":3,"name":"Ali Mohsin Ahmed Al-Sabaawi","email":"","orcid":"","institution":"Ninevah University","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"Mohsin Ahmed","lastName":"Al-Sabaawi","suffix":""},{"id":531269057,"identity":"9c359e16-d5ff-4f89-91a8-f26ef72c5a84","order_by":4,"name":"Hussein M. 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