A Deep Learning Technique in Cardio Vascular Disease Prediction Using Convolutional Neural Network
Heart disease or Cardio-vascular disease is considered as a fatal illness that continues to increase faster in our modern world, in 2012, around 17.5 million individuals kicked the bucket from coronary illness, implying that it comprises of the 31% of every single worldwide passing. Besides, coronary illness loss of life rises each year. This research aims at applying and improving a deep learning technique to detect Cardio-Vascular Disease using 1D Convolutional Neural Network, to also evaluate the performance of the proposed system and compare it with the existing system. Since medical big data has been increasing daily and data storage costs decreasing, deep learning algorithms can play an important role in processing these medical data and predicting diseases. With the help of the deep learning (CNN) Classifier algorithm, the research was able to build a deep-learning model. We obtained a precision of 83.9% a recall of 83.9% and an F-Measure of 83.9% which shows that our proposed system outperforms the existing system.
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