Abstract
Background and Aims : The etiology behind atherosclerosis is complex, involving many different processes, and develops over several years, often without symptoms, before it leads to more acute conditions such as stroke. One way of dealing with this complexity is through mathematical modelling. There already exist models for relevant organs and sub-systems. However, none have combined these models for different sub-systems and personalized them into digital twins.
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