Fuzzy Logic Based Decision Support Systems for Medical Diagnosis


  • Mule Shrishail Basvant Associate Professor, Department of Electronics & Telecommunication Engineering, Sinhgad College of Engineering, Pune-41
  • Kamatchi K. S., Assistant Professor, Department of IT, Sathyabama Institute of Science and Technology, Chennai
  • A. Deepak Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamilnadu
  • Manish Sharma Associate Professor, Department of Computer Science & Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand
  • 5Rakesh Kumar Department of Computer Engineering & Applications, GLA University, Mathura
  • Vijay Kumar Yadav Lloyd Institute of Engineering & Technology, Greater Noida
  • Akhil Sankhyan Lloyd Law College, Greater Noida
  • Anurag Shrivastava Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamilnadu


Sugeno FIS, Decision Support Systems, Fuzzy Logic, Medical Diagnosis, Mamdani FIS


This research pioneers the integration of fuzzy rationale into choice-back frameworks for the restorative conclusion, drawing motivation from later headways within the field. Utilizing the Mamdani Fuzzy Inference Framework, the study centers on progressing symptomatic exactness and interpretability in healthcare scenarios. A comparative investigation with the Sugeno FIS gives experiences into the qualities and shortcomings of distinctive fuzzy induction frameworks. Emphasizing real-world pertinence and moral contemplations, the investigation proposes an open-source execution, cultivating collaboration and straightforwardness. Essential commitments from related studies, crossing maturing forecast, kidney disease determination, and rest apnea discovery, educate the research's direction. Future work points to extending the comparative investigation, investigating hybrid approaches, and coordinating logical manufactured insights procedures, guaranteeing the proposed framework advances with developing advances. The investigation envisions a dynamic commitment to the progressing advancement of clever choice bolster frameworks in therapeutic conclusion.


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How to Cite

Basvant, M. S. ., K. S., K. ., Deepak, A. ., Sharma, M. ., Kumar, 5Rakesh ., Yadav, V. K. ., Sankhyan, A. ., & Shrivastava, A. . (2024). Fuzzy Logic Based Decision Support Systems for Medical Diagnosis. International Journal of Intelligent Systems and Applications in Engineering, 12(15s), 01–07. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4701



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