The rising costs of healthcare in contemporary society have raised significant concerns, and efficiently identifying medical risks is essential to reducing treatment expenses and improving overall health outcomes. The process of assessing the risk of current diseases involves multiple tests, requires the expertise of medical professionals, and is time-consuming and costly. As a result of these challenges, artificial intelligence techniques have been used in the diagnosis of many diseases, including diabetes, which is one of the most widespread chronic diseases in the world and affects many people. The method of combining fuzzy logic with artificial intelligence techniques is one of the most accurate ways to detect diabetes.