Utilizing the Heterogeneity of Clinical Data for Model Refinement and Rule Discovery Through the Application of Genetic Algorithms to Calibrate a High-Dimensional Agent-Based Model of Systemic Inflammation.

Frontiers in Physiology
Chase Cockrell, Gary An

Abstract

Introduction: Accounting for biological heterogeneity represents one of the greatest challenges in biomedical research. Dynamic computational and mathematical models can be used to enhance the study and understanding of biological systems, but traditional methods for calibration and validation commonly do not account for the heterogeneity of biological data, which may result in overfitting and brittleness of these models. Herein we propose a machine learning approach that utilizes genetic algorithms (GAs) to calibrate and refine an agent-based model (ABM) of acute systemic inflammation, with a focus on accounting for the heterogeneity seen in a clinical data set, thereby avoiding overfitting and increasing the robustness and potential generalizability of the underlying simulation model. Methods: Agent-based modeling is a frequently used modeling method for multi-scale mechanistic modeling. However, the same properties that make ABMs well suited to representing biological systems also present significant challenges with respect to their construction and calibration, particularly with respect to the selection of potential mechanistic rules and the large number of associated free parameters. We have proposed that machine learning ...Continue Reading

References

May 16, 2002·Proceedings of the National Academy of Sciences of the United States of America·Eric Bonabeau
Aug 28, 2004·Trends in Biotechnology·Marie Csete, John Doyle
Apr 10, 2007·Cellular Immunology·V BaldazziM Bernaschi
Sep 14, 2010·Wiley Interdisciplinary Reviews. Systems Biology and Medicine·Gary AnYoram Vodovotz
Oct 3, 2018·Burns : Journal of the International Society for Burn Injuries·Maria BergquistMiklos Lipcsey
Jan 27, 2019·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Brenden K PetersenDaniel M Faissol

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IIRABM

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