  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.
