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deep learning to discovered a group of heart conditions through Echocardiography

This project introduces echocardiography to discover a group of patients with a variety of heart conditions including lower fibrillation, coronary artery disease, cardiomyopathy, aortic valve stenosis and amyloidosis
This program outperforms human experts in diagnosing patients with serious disease
It uses the left ventricular cardiac functions which is used to diagnose cardiomyopathy through a wide range of videos 10030 Anatomical Echocardiography by EchoNet

Normal Low Ejection Fraction Arrhythmia
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The results were conducted by three patients who had normal cardiac functions in the left column and three who had low expulsion fractures as you see in the middle column where the color blue is greater than normal and three of them in the right column suffer from arrhythmias (as you see in the photo once, it beats properly and again strongly and once Varying)

The project discovers and predicts three heart conditions:

  • Divide the left ventricle
  • Predicting a fracture of premature ejaculation
  • And cardiomyopathy by predictions that each beats

This project introduces the EchoNet-Dynamic Data Set, a publicly available data set from unspecified Echocardiogram videos, available at https://echonet.github.io/dynamic/.

The code is available on
https://github.com/echonet/dynamic

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