Artificial Intelligence-Enabled Heart Disease Prediction Using Genetic Evolutionary Heart Disease Optimization from Internet-of-Things Sensors

Abstract

Today, heart disease is one of the most important causes of death in the world. Therefore, the prediction and early diagnosis are important in supporting treatment time in a medical field. It reduces death and incurs less medical expenses. Cardiovascular disease (CVD), despite significant advances in the diagnosis and treatment, is still a major cause of morbidity and mortality worldwide. The heart rate, blood pressure, and temperature of the patient have carried during the testing phase through the Internet-of-Things setup. Artificial intelligence techniques such as depth learning and machine learning can improve medical knowledge due to unlocking the clinically relevant information and increasing the complexity of data. CVD brings a heavy burden on the whole of the patient and society. Therefore, to provide effective treatment options, there is a need to improve the diagnosis and treatment of cardiovascular disease. Regarding the above issues, the Genetic Evolutionary Heart Disease Optimization algorithm is proposed in this work; it uses the new communication and information technology to create universal health-care services and apply it to cardiovascular diseases and it also offers the potential to doctors in the heart and clinical practice.