| Popis: |
The medical deep learning is considered one of the important analysis techniques and many evolutionary techniques and algorithms that have been improved to extract the features of images or classify and diagnose the different types of medical data. On another hand, deep learning is more practical especially for the classification process and it is noticed in speed and accuracy. In this paper, we apply different algorithms of deep learning such as Alex net and google net. Furthermore, we will test the algorithms on big data and try to achieve the result at a minimum time as possible. The second target of this paper is how to apply some of machine learning methods for ECG big data. Finally, we compare the results of the methods of deep learning and machine learning to obtain the best accuracy in classification. The accuracy of deep learning classification achieved 96.5% and more accurate in big data on CPU and machine learning approved good accuracy but we divide the data into parts. Deep learning takes big data without separating it. Based on the previous, deep learning achieved suitable results in ECG big data. |
