Predicting long-term ablation targets for ventricular arrhythmia; the evolution with computational cardiology – Correspondence

Moinuddin, Arsalan ORCID: https://orcid.org/0000-0002-4242-1714, Sethi, Yashendra, Goel, Ashish and Uniyal, Nidhi (2022) Predicting long-term ablation targets for ventricular arrhythmia; the evolution with computational cardiology – Correspondence. International Journal of Surgery, 108. ART 106987. doi:10.1016/j.ijsu.2022.106987

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Abstract

Letter to the editor.

Item Type:	Article
Article Type:	Editorial
Uncontrolled Keywords:	Cardiovascular diseases; CVD; Ventricular arrhythmia; Computational cardiology
Subjects:	G Geography. Anthropology. Recreation > GV Recreation Leisure > GV557 Sports Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine
Divisions:	Schools and Research Institutes > School of Education and Science
Depositing User:	Anna Kerr
Date Deposited:	28 Nov 2022 14:17
Last Modified:	20 Nov 2024 13:04
URI:	https://eprints.glos.ac.uk/id/eprint/11895

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