Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Bavirthi, Swathi Sowmya; Manikandan, M.; Rajagopal, Manikandan; Leelavathy, S.; Rao, K. Srinivas Title A name given to the resource Fuzzy Computational Intelligence in Personalized Medicine and Diagnosis Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Fuzzy Information and Engineering;Volume;17;Issue;4;pp.472-483 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.26599/FIE.2025.9270073" target="_blank" rel="noreferrer noopener">https://doi.org/10.26599/FIE.2025.9270073</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105027403258?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105027403258?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Bavirthi S.S., Chaitanya Bharathi Institute of Technology, IT Dept., Hyderabad, 500075, India; Manikandan M., School of Computing, SRM Institute of Science and Technology, Faculty of Engineering and Technology, Department of Computational Intelligence, Chennai, 603203, India; Rajagopal M., School of Business and Management, Christ university, Bangalore, 560029, India; Leelavathy S., Department of AI&amp;DS, Panimalar engineering college, Chennai, 503200, India; Rao K.S., MLR Institute of Technology, Department of Computer Science and Engineering, Hyderabad, 722003, India Description An account of the resource The development of fuzzy computational intelligence (FCI) has emerged as an effective method for personalized medicine and diagnosis. FCI effectively handles uncertainty and imprecision in medical data, facilitating patient-specific treatment recommendations. Conventional diagnostic and treatment methods typically rely on fixed threshold-based approaches, which fail to account for individual variations in patient responses, leading to suboptimal treatment outcomes. This study proposes the personalized treatment recommendation using fuzzy logic (PTR-FC) framework for diabetes (DB) patients to address these challenges. The framework integrates patient-specific data such as blood glucose levels, diet, exercise, and medication history into the fuzzy inference system (FIS), supporting personalized treatment recommendations. The treatment plans are dynamically adapted based on individual patient outcomes using linguistic factors and fuzzy rules (FR). The proposed method dynamically adjusts recommendations in real time, potentially enhancing personalized treatment and improving decision-making in DB management. Additionally, it promotes lifestyle modifications while reducing the risk of medication-induced complications. The effectiveness of the proposed method was compared to conventional methods, demonstrating improved treatment accuracy, increased patient adherence, and reduced adverse health risks. The PTR-FC framework offers a more adaptive and effective approach to DB management, ensuring better patient outcomes. 2009 Tsinghua University Press. Subject The topic of the resource computational intelligence; diabetes management; fuzzy logic (FL); medical decision support; personalized medicine; treatment optimization Publisher An entity responsible for making the resource available Tsinghua University Press Relation A related resource ISSN: 16168658; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online