Dynamic Data-Driven Modeling for Ex Vivo Data Analysis: Insights into Liver Transplantation and Pathobiology
AbstractExtracorporeal organ perfusion, in which organs are preserved in an isolated, ex vivo environment over an extended time-span, is a concept that has led to the development of numerous alternative preservation protocols designed to better maintain organ viability prior to transplantation. These protocols offer researchers a novel opportunity to obtain extensive sampling of isolated organs, free from systemic influences. Data-driven computational modeling is a primary means of integrating the extensive and multivariate data obtained in this fashion. In this review, we focus on the application of dynamic data-driven computational modeling to liver pathophysiology and transplantation based on data obtained from ex vivo organ perfusion. View Full-Text
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Sadowsky, D.; Abboud, A.; Cyr, A.; Vodovotz, L.; Fontes, P.; Zamora, R.; Vodovotz, Y. Dynamic Data-Driven Modeling for Ex Vivo Data Analysis: Insights into Liver Transplantation and Pathobiology. Computation 2017, 5, 46.
Sadowsky D, Abboud A, Cyr A, Vodovotz L, Fontes P, Zamora R, Vodovotz Y. Dynamic Data-Driven Modeling for Ex Vivo Data Analysis: Insights into Liver Transplantation and Pathobiology. Computation. 2017; 5(4):46.Chicago/Turabian Style
Sadowsky, David; Abboud, Andrew; Cyr, Anthony; Vodovotz, Lena; Fontes, Paulo; Zamora, Ruben; Vodovotz, Yoram. 2017. "Dynamic Data-Driven Modeling for Ex Vivo Data Analysis: Insights into Liver Transplantation and Pathobiology." Computation 5, no. 4: 46.
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