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Deep Learning for ECG Synthesis
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One of the major causes of death is cardiovascular diseases. In 2019, it reached 32% of all deaths worldwide. ECG is widely used in the diagnosis of cardiovascular diseases mostly since it is non-invasive and painless. Diagnosis is usually performed by human specialists which is timeconsuming
and prone to human error, in case of availability. However, automatic ECG diagnosis is becoming increasingly more acceptable since not only it eliminates randomized human errors, butalso it can be available as a bedside testing any time and anywhere using common and affordable
wearable heart monitoring devices. Automatic ECG diagnosis algorithms are usually deep neural network classifier models which classify the ECG beats depending on the general pattern of the ECG heartbeat
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