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

ElRefai, MAbouelasaad, MWiles, BMDunn, AJConiglio, SZemkoho, ABRoberts, PR2024-05-072024-05-072025-10ElRefai, M, Abouelasaad, M, Wiles, BM, Dunn, AJ, Coniglio, S, Zemkoho, AB & Roberts, PR 2025, 'Deep learning-based insights on T:R ratio behaviour during prolonged screening for S-ICD eligibility', Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing, vol. 68, no. 7, pp. 1387-1397. https://doi.org/10.1007/s10840-022-01245-6ORCID: /0000-0002-1226-5335/work/113027395https://hdl.handle.net/2164/23416Dr. Mohamed ElRefai is receiving unrestricted grant from Boston Scientific. Dr. Benedict Wiles has received unrestricted research funding and consultancy payments from Boston Scientific. Dr. Paul Roberts receives consultancy fees from Boston Scientific and Medtronic. The other authors declare no competing interests.111013231engsubcutaneous implantable cardiac defibrillatordeep learning methodsartificial intelligencecardiac devicesR MedicineRDeep learning-based insights on T:R ratio behaviour during prolonged screening for S-ICD eligibilityJournal article10.1007/s10840-022-01245-6http://europepmc.org/abstract/med/35551558