Reducing noise of intracardiac electrocardiograms using an autoencoder and utilizing and refining intracardiac and body surface electrocardiograms using deep learning training loss functions
A loss function, noise reduction automatic coding technology, applied in the direction of medical automatic diagnosis, instrumentation, application, etc.
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[0026] This paper discloses a system for exploiting and refining intracardiac and surface ECGs using one or more deep learning training loss functions (i.e., types of artificial intelligence and machine learning operations), generally referred to herein as training algorithm. The training algorithm for the system utilizing and refining intracardiac and surface electrocardiograms is processor executable code or software necessarily derived from the processing operations and processing hardware of the medical device equipment to provide Improved ECG and intracardiac ECG for the treatment of cardiac disorders. According to one embodiment, the training algorithm provides a specific training method for the medical device equipment and the autoencoder therein. This particular training method involves multi-step data manipulation of the electrical signal of the heart that emphasizes clinically significant regions or events within the electrical signal (eg, potential origin locations...
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