Engineering Noorul Islam Center for Higher Education

Kanniyākumāri, India

Engineering Noorul Islam Center for Higher Education

Kanniyākumāri, India

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Seenivasagam V.,Engineering National Engineering College | Chitra R.,Engineering Noorul Islam Center for Higher Education
Neural Network World | Year: 2016

Myocardial Infarction (MI) also known as heart attack is one of the most dangerous cardiovascular diseases. Accurate early prediction can effectively reduce the mortality rate caused by MI. The early stages of MI may only have subtle indications which can be varied in variable risk factors and making diagnosis difficult even for experienced cardiologists. In this paper the computer aided detection system is proposed to find the risk level of MI using the supervised classifier. The MI prediction system is developed using Feed Forward Neural Network (FFNN), Cascade Correlation Neural Network (CNN), and Support Vector Machine (SVM). Genetic Optimized Neural Network (GAANN), Particle Swarm Optimized Neural Network (PSONN) and also the performance of the Computer Aided Detection system is analyzed using various performance metrics. © 2016 CTU FTS.

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