A proposed application utilizing neural networks aims to predict heart disease vulnerability based on basic clinical parameters such as age, sex, and pulse rate.
With the rampant increase in the heart stroke rates at juvenile ages, we need to put a system in place to be able to detect the symptoms of a heart stroke at an early stage and thus prevent it. It is impractical for a common man to frequently undergo costly tests like the ECG and thus there needs to be a system in place which is handy and at the same time reliable, in predicting the chances of a heart disease. Thus we propose to develop an application which can predict the vulnerability of a heart disease given basic symptoms like age, sex, pulse rate etc. The machine learning algorithm neural networks has proven to be the most accurate and reliable algorithm and hence used in the proposed system.
Gavhane et al. (Thu,) conducted a other in Heart disease. Machine learning application (neural networks) was evaluated on Prediction of heart disease vulnerability. A proposed application utilizing neural networks aims to predict heart disease vulnerability based on basic clinical parameters such as age, sex, and pulse rate.