A computational model-based framework to plan clinical experiments – an application to vascular adaptation biology

Stefano Casarin, Scott A. Berceli, Marc Garbey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Several computational models have been developed in order to improve the outcome of Vein Graft Bypasses in response to arterial occlusions and they all share a common property: their accuracy relies on a winning choice of the coefficients’ value related to biological functions that drive them. Our goal is to optimize the retrieval of these unknown coefficients on the base of experimental data and accordingly, as biological experiments are noisy in terms of statistical analysis and the models are typically stochastic and complex, this work wants first to elucidate which experimental measurements might be sufficient to retrieve the targeted coefficients and second how many specimens would constitute a good dataset to guarantee a sufficient level of accuracy. Since experiments are often costly and time consuming, the planning stage is critical to the success of the operation and, on the base of this consideration, the present work shows how, thanks to an ad hoc use of a computational model of vascular adaptation, it is possible to estimate in advance the entity and the quantity of resources needed in order to efficiently reproduce the experimental reality.

Original languageEnglish (US)
Title of host publicationComputational Science – ICCS 2018 - 18th International Conference, Proceedings
EditorsHaohuan Fu, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Peter M. Sloot, Jack Dongarra, Yong Shi, Yingjie Tian
PublisherSpringer-Verlag
Pages352-362
Number of pages11
ISBN (Print)9783319936970
DOIs
StatePublished - 2018
Event18th International Conference on Computational Science, ICCS 2018 - Wuxi, China
Duration: Jun 11 2018Jun 13 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10860 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Computational Science, ICCS 2018
CountryChina
CityWuxi
Period6/11/186/13/18

Keywords

  • Agent based model
  • Experiment planning
  • Virtual dataset

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'A computational model-based framework to plan clinical experiments – an application to vascular adaptation biology'. Together they form a unique fingerprint.

Cite this