Timely detection of illnesses is vital to prevent severe infections and ensure effective treatment, as it's always better to prevent diseases than to cure them. Sadly, many patients remain undiagnosed until their conditions worsen, resulting in high death rates. Expert systems offer a solution by automating early-stage diagnoses using a fuzzy rule-based approach. Our study gathered data from various sources, including hospitals, to develop an expert system aimed at identifying early signs of diseases, particularly heart conditions. The diagnostic process involves collecting and processing test results using the expert system, which categorizes disease risks and aids physicians in treatment decisions. By incorporating expert systems into clinical practice, we can improve the accuracy of disease detection and address challenges in patient management, particularly in areas with limited medical resources.
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