Survey of Fuzzy-Logic based algorithms for the Risk of Heart Disease Detection

The medical sciences rely heavily on machine learning, artificial intelligence (AI), fuzzy logic, neural networks, genetic algorithms (GA), and their hybrid methods to accurately identify a variety of disorders in patients. In the modern world, heart-related issues are quite prevalent. As extra cholesterol builds up in the arteries and blood vessels, the chance of heart failure increases. This condition is characterized by tiredness, chest discomfort, dyspnea, trouble sleeping, and depression. It also increases the risk of heart attack and stroke. This study intends to review several studies on fuzzy logic (FL) and hybrid-based methods for assessing patient risk for heart disease. The current research lists articles from ۲۰۱۰ together with the power, accuracy, rate operating system, and other requirements employed in the diagnosis of heart disease using FL and Hybrid-based techniques. This poll encourages researchers to come up with new, creative ideas and to go on with their work in the relevant sector.

کلیدواژه ها:

Heart disease ، Fuzzy Logic ، Artificial intelligence (AI)