Enhancement of Coronary Heart Disease Prediction using Stacked Long Short Term Memory - Cinthiya, Cinthiya; Oetama, Raymond Sunardi (Universitas Merdeka Malang, 2023)
The high incidence of death caused by coronary heart disease has become a global concern in the world of health, where patients with coronary heart disease are no longer only adults and the elderly, yet there are now so many cases of coronary heart disease experienced by underage patients. As a result, it is critical to be able to prevent and reduce the number of instances. One of them is the ability to predict a person's risk of coronary heart disease so that patients can be treated and provided early therapy. The risk of coronary heart disease will be predicted in this study utilizing Stacked long short-term memory algorithms. By appling this algorithm, the accuracy of 81.3% from previous study can be increased to 91.8% by this study.Â