Deep learning-based insights on T:R ratio behaviour during prolonged screening for S-ICD eligibility.

Mohamed ElRefaiMohamed AbouelasaadBenedict M WilesAnthony J DunnStefano ConiglioAlain B ZemkohoPaul R Roberts

Published in: Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing (2022)

We propose adopting prolonged screening to select patients eligible for S-ICD with low probability of TWO and inappropriate shocks. The appropriate T:R ratio likely lies between 1:3 and 1:1. Further studies are required to identify the optimal screening thresholds.

Keyphrases

deep learning
end stage renal disease
newly diagnosed
ejection fraction
chronic kidney disease
peritoneal dialysis
machine learning
artificial intelligence
convolutional neural network
patient reported