Study of ECG Analysis based Cardiac Disease Prediction using Deep Learning Techniques
Keywords:
Cardiovascular disease, Deep learning, Electrocardiogram, Neural networksAbstract
A quarter percent of mortality rates over the world is due to cardiovascular diseases which is 32% over the world population such that approximately 17.9 million. One of such CVD is arrhythmia disease. Faster prediction of heart disease may reduce the chances of death rates. This necessities us to predict the CVD using advanced techniques like deep learning and machine learning.This study presents the various types of deep learning methods for the prediction of CVD. In deep learning, convolutional neutral network is considered to be the best technique which results in 94.2% in training as well as testing accuracy. Deep learning structures its algorithm to make Artificial neutral network that predicts intelligent decisions from dataset. ECG is a good specification used for the detection of cardio disease. Deep learning is the most commonly used method because for its accurate prediction, better sensitivity, specificity and highest prediction performance. CNN, Auto encoder and LSTM methods are found to give good accuracy results than other deep learning techniques.
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