Dunn, Anthony J.Coniglio, StefanoElRefai, MohamedRoberts, Paul R.Wiles, Benedict M.Zemkoho, Alain B.2023-10-312023-10-312023-09Dunn, A J, Coniglio, S, ElRefai, M, Roberts, P R, Wiles, B M & Zemkoho, A B 2023, 'Deep learning and hyperparameter optimization for assessing one’s eligibility for a subcutaneous implantable cardioverter-defibrillator', Annals Of Operations Research, vol. 328, pp. 309-335. https://doi.org/10.1007/s10479-023-05326-10254-5330ORCID: /0000-0002-1226-5335/work/146067848https://hdl.handle.net/2164/22072Open access funding provided by Università degli studi di Bergamo within the CRUI-CARE Agreement. The work of Anthony J. Dunn is jointly funded by Decision Analysis Services Ltd andf EPSRC through the studentship with Reference EP/R513325/1. The work of Alain B. Zemkoho is supported by the EPSRC grant EP/V049038/1. The work of Stefano Coniglio and Alain B. Zemkoho is supported by The Alan Turing Institute under the EPSRC grants EP/N510129/1 and EP/W037211/1.272182939engSDG 3 - Good Health and Well-beingDeep learningMachine learningOptimizationSubcutaneous implantable cardioverter defibrillatorsR MedicineGeneral Decision SciencesManagement Science and Operations ResearchEngineering and Physical Sciences Research Council (EPSRC)EP/R513325/1EP/V049038/1EP/N510129/1EP/W037211/1RJournal article10.1007/s10479-023-05326-1http://www.scopus.com/inward/record.url?scp=85160251694&partnerID=8YFLogxK328