@article{5424206856e04e7a811f4f552e1a340b,
title = "A twofold usage of an agent-based model of vascular adaptation to design clinical experiments",
abstract = "Several computational models of Vein Graft Bypass (VGB) adaptation have been developed in order to improve the surgical outcome and they all share a common property: their accuracy relies on a winning choice of their driving coefficients which are best to be retrieved from experimental data. Since experiments are time-consuming and resources-demanding, the golden standard is to know in advance which measures need to be retrieved on the experimental table and out of how many samples. Accordingly, our goal is to build a computational framework able to pre-design an effective experimental structure to optimize the computational models setup. Our hypothesis is that an Agent-Based Model (ABM) developed by our group is comparable enough to a true set of experiments to be used to generate reliable virtual experimental data. Thanks to a twofold usage of our ABM, we created a filter to be posed before the real experiment in order to drive its optimal design. This work is the natural continuation of a previous study from our group [1], where the attention was posed on simple single-cellular events models. With this new version we focused on more complex models with the purpose of verifying that the complexity of the experimental setup grows proportionally with the accuracy of the model itself.",
keywords = "Agent-based model, Experiment planning, Virtual dataset",
author = "Stefano Casarin and Berceli, {Scott A.} and Marc Garbey",
note = "Funding Information: The NIH grant U01HL119178-01 supported this research. Funding Information: Stefano Casarin, PhD is a postdoctoral fellow with the Center for Computational Surgery at Houston Methodist Research Institute. He received his MS in biomedical engineering from Politecnico di Milano, Italy in 2013 and his PhD in fluid mechanics from Universite de La Rochelle, France in 2017. His work, under the mentorship of dr. Marc Garbey and dr. Scott Berceli, mostly focuses on the development of computational models to improve the outcome of vascular therapies and treatments in response to arterial occlusive diseases. His work is supported by NIH and he has been publishing in journals in the field of computational science and theoretical biology. Funding Information: Scott A. Berceli, MD, PhD is a Professor of Surgery at University of Florida and a vascular surgeon at the Malcom Randall Veterans Affairs Medical Center and Shands Hospital of Gainseville, Florida. He received his medical degree from University of Pittsburgh School of Medicine and his PhD in chemical engineering from the same school. He has published extensively in high impact factor journal of vascular surgery. His work has been continuously funded by NIH. Funding Information: Marc Garbey, PhD is the scientific director of MITIE and chair of the Center for Computational Surgery at Houston Methodist Research Institute. He former was a professor in biology, mathematics and computer science at University of Houston. He received his PhD from Ecole Centrale de Lyon, France in applied mathematics in 1984. His work in computational surgery is funded by NSF and NIH. He has about 200 referred publications published mainly in journal of mathematics, computer science, mechanic, biology and medicine. Publisher Copyright: {\textcopyright} 2018 Elsevier B.V. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.",
year = "2018",
month = nov,
doi = "10.1016/j.jocs.2018.09.013",
language = "English (US)",
volume = "29",
pages = "59--69",
journal = "Journal of Computational Science",
issn = "1877-7503",
publisher = "Elsevier",
}