The Fuzzy Inference Systems (FIS) have proven to be an important tool in the imprecision and relevant manipulation indeterminacy, especially in the field of medical diagnosis where humans are able to think discretionally decision-making is necessary. The increase in health care data and the necessity of explainable AI have increased the interest of researchers in creation and advancement of fuzzy inference techniques. There is a growing interest among scholars in inference models of various kinds the knowledge of the most essential factors that predetermine the choice of the best inferencing mechanisms. Here, the current paper examines the intellectual organization and history of development of research fuzzy inference systems with particular focus on their medical diagnosis applications. The experimentally analyzes central thematic domains, increasing publication, referencing tendencies, top publication sources, major contributors, and keywords that keep on reoccurring in this area. It further identifies the gaps in research at hand and describes the future directions of the research exploration. The approach that this study takes in a methodological sense is a dual one; it is a combination of Systematic Bibliometric analysis and Literature Review (SLR). There are 619 research articles contained in the dataset databases, such as ScienceDirect, are the major source of information, and the choice of entries is made based on their relevance scholarly literature, dating back to 2000-2025. The outcomes are informative into the current research focus and intellectual premises which have informed the fuzzy inference in medical diagnosis.
Keywords: Fuzzy Inference Systems (FIS), uncertainty, decision-making, fuzzy inference techniques, AI, medical diagnosis, Systematic Literature Review (SLR), Bibliometric analysis
How to cite this article: Kapoor R, Bedi SS, Singh YP, Fuzzy Inference Techniques in Medical Diagnosis: Bibliometric Analysis and a Systematic Literature Review. Int J Drug Deliv Technol. 2026;16(4s): 344-365; DOI: 10.25258/ijddt.16.4s.45