Role of deep learning methods in screening for subcutaneous implantable cardioverter defibrillator in heart failure.
Mohamed ElRefaiMohamed AbouelasaadBenedict M WilesAnthony J DunnStefano ConiglioAlain B ZemkohoJohn M MorganPaul R RobertsPublished in: Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc (2022)
T:R ratio, a main determinant for S-ICD eligibility, is higher and has more tendency to fluctuate in HF patients undergoing diuresis. We hypothesize that our novel neural network model could be used to select HF patients eligible for S-ICD by better characterization of T:R ratio reducing the risk of T-wave over-sensing (TWO) and inappropriate shocks. Further work is required to consolidate our findings before applying to clinical practice.