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"Cardiac arrest occurs when the heart muscle does not develop properly, resulting in a sudden loss of blood supply. " The ECG signal is one of the most commonly used methods for detecting cardiac electrical activity, and it is used to find heart block. The stages of ECG signal pre-processing involve denoised algorithms and extracting specific characteristics from clean ECG predicting cardiac arrest in an early stage," says Denoised.
"Methods: We invented a machine learning algorithm to automatically predict the circulatory state during cardiac arrest care from 4-second-long snippets of accelerometry and electrocardiogram results obtained from real-world defibrillator records. " The algorithm was developed based on 917 cases from the German Resuscitation Registry, for which ground truth labels were created by a manual annotation of physicians. Conclusion and significance: The algorithm can be used to simplify retrospective annotation for quality control and, in addition, to encourage physicians to monitor circulatory status during cardiac arrest therapy. ".
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