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.

翻译：疾病的及时检测对于预防严重感染并确保有效治疗至关重要，因为防病始终优于治病。遗憾的是，许多患者在病情恶化前未能得到诊断，导致死亡率居高不下。专家系统通过采用基于模糊规则的方法实现早期诊断自动化，为此提供了解决方案。本研究从包括医院在内的多种来源收集数据，旨在开发一套用于识别疾病早期征兆（尤其是心脏疾病）的专家系统。诊断流程包括通过专家系统收集并处理检测结果，该系统可对疾病风险进行分类，并辅助医生制定治疗决策。将专家系统融入临床实践，能够提升疾病检测的准确性，并解决患者管理中的难题，尤其在医疗资源有限的地区。