Correlation analysis of deep learning methods in S‐ICD screening

Abstract

Machine learning methods are used in the classification of various cardiovascular diseases through ECG data analysis. The concept of varying subcutaneous implantable cardiac defibrillator (S‐ICD) eligibility, owing to the dynamicity of ECG signals, has been introduced before. There are practical limitations to acquiring longer durations of ECG signals for S‐ICD screening. This study explored the potential use of deep learning methods in S‐ICD screening.