{"id":12568,"date":"2023-07-12T14:05:16","date_gmt":"2023-07-12T12:05:16","guid":{"rendered":"https:\/\/new.sano.science\/?post_type=research&#038;p=12568"},"modified":"2024-01-05T14:00:04","modified_gmt":"2024-01-05T13:00:04","slug":"the-eurvalve-model-execution-environment","status":"publish","type":"research","link":"https:\/\/sano.science\/research\/the-eurvalve-model-execution-environment\/","title":{"rendered":"The EurValve model execution environment\u00a0"},"content":{"rendered":"\n<h2 class=\"wp-block-heading eplus-wrapper\">Bubak, M; Czechowicz, K; Guba\u0142a, T; Hose, D R; Kasztelnik, M; Malawski, M; Meizner, J; Nowakowski, P; Wood, S<\/h2>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n<p class=\" eplus-wrapper\">The goal of this paper is to present a dedicated high-performance computing (HPC) infrastructure which is used in the development of a so-called reduced-order model (ROM) for simulating the outcomes of interventional procedures which are contemplated in the treatment of valvular heart conditions. Following a brief introduction to the problem, the paper presents the design of a model execution environment, in which representative cases can be simulated and the parameters of the ROM fine-tuned to enable subsequent deployment of a decision support system without further need for HPC. The presentation of the system is followed by information concerning its use in processing specific patient cases in the context of the EurValve international collaboration.<\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n\t\n    \n        \n\t\t\t<a href=\"https:\/\/royalsocietypublishing.org\/doi\/10.1098\/rsfs.2020.0006\" target=\"_blank\" rel= \"noopener noreferrer nofollow\" class=\"button primary \">\n\n\t\t\t\t<span>\n\t\t\t\t\tREAD HERE\n\t\t\t\t<\/span>\n\n\t\t\t<\/a>\n\n        \n    \n","protected":false},"excerpt":{"rendered":"<p>In: Interface Focus, vol. 11, no. 1, pp. 20200006, 2021, ISSN: 2042-8898.<\/p>\n","protected":false},"featured_media":0,"template":"","research_type":[8],"research_team":[16],"class_list":["post-12568","research","type-research","status-publish","hentry","research_type-publications","research_team-extreme-scale-data-and-computing"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.3 (Yoast SEO v27.3) - 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