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Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention

Overview of attention for article published in Annals of Biomedical Engineering, May 2016
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Title
Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention
Published in
Annals of Biomedical Engineering, May 2016
DOI 10.1007/s10439-016-1628-0
Pubmed ID
Authors

Yanhang Zhang, Victor H. Barocas, Scott A. Berceli, Colleen E. Clancy, David M. Eckmann, Marc Garbey, Ghassan S. Kassab, Donna R. Lochner, Andrew D. McCulloch, Roger Tran-Son-Tay, Natalia A. Trayanova

Abstract

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications.

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Geographical breakdown

Country Count As %
Spain 1 <1%
Chile 1 <1%
Germany 1 <1%
Unknown 152 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 25%
Researcher 22 14%
Student > Master 13 8%
Student > Bachelor 13 8%
Student > Doctoral Student 10 6%
Other 30 19%
Unknown 28 18%
Readers by discipline Count As %
Engineering 59 38%
Medicine and Dentistry 17 11%
Computer Science 10 6%
Agricultural and Biological Sciences 5 3%
Mathematics 4 3%
Other 18 12%
Unknown 42 27%