Predictive Heart Disease Diagnosis System with CNN Algorithm and Expert System for Indonesian Patients

Cardiovascular disease, a major global health concern, encompasses heart and blood vessel dysfunctions leading to stroke, heart attack, and hypertension, resulting in significant mortality worldwide. In 2019 alone, it claimed approximately 17.9 million lives, with 85% attributed to heart attacks and strokes. In Indonesia, heart disease, including stroke and coronary conditions, is a prevalent cause of death, particularly in urban areas, with a diagnosed prevalence of 1.5% in 2018. However, many at-risk individuals in Indonesia lack adequate treatment. Addressing this issue, this study aims to develop a web-based predictive system for heart disease diagnosis and an expert system for heart failure patients. Leveraging recurrent neural network algorithms and the 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure, the systems offer accurate diagnostics, with the predictive system achieving an accuracy rate of 91.6%, and tailored recommendations. Integration into a user-friendly application facilitates accessible healthcare solutions.