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Deep Learning for ECG Diagnosis by Satish Padimila is a document available to read on EtoBox.

What is Deep Learning for ECG Diagnosis about?

The paper introduces a deep learning method for automatic ECG diagnosis, utilizing a Deep Convolution Neural Network (D-CNN) and KNN classifier to detect Atrial fibrillation and congestive heart failure, achieving an accuracy of 98%. It emphasizes the significance of heart disease as a leading cause of death globally and discusses various classification techniques, including the effectiveness of data augmentation. The study highlights the importance of early diagnosis and treatment of arrhythmias and heart

Author

Satish Padimila

Language

EN