Fuzzy Logic Based Lipid Profile Control System

The rapid advancement of technology and the diverse landscape of medical information has underscored the necessity for intelligent systems to assist medical practitioners in decision-making by harnessing human knowledge and reasoning capabilities. Disease diagnosis process is very complicated and full of uncertainty as one symptom can lead to different diseases and one disease may contains many symptoms. This system should mitigate uncertainty and ambiguity for healthcare practitioners while improving the accuracy of diagnoses. Medical tests are pivotal for practitioners in identifying diseases and determining their progression. In our study, we present a resilient and effective system capable of processing diverse inputs from Lipid profile, providing highly dependable outputs for medical condition diagnosis and treatment decisions. Fuzzy systems possess the capability to represent the inherent uncertainties of human knowledge through the use of linguistic variables. Their results are easily interpretable due to the natural representation of rules, and the knowledge base can be easily extended by adding new rules. Additionally, fuzzy systems exhibit robustness in the face of potential disturbances in the system. The system utilizes medical test report data as input, and experiments are conducted using the MATLAB R2021a, with execution carried out in Visual Studio 2019 using C#. The simulation results closely correspond to the designed model, demonstrating relative errors that fall within an acceptable range. The outcomes of the proposed system will prove beneficial in the medical domain by furnishing doctors with precise information about a patient's health status.