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Dynamic Data-Driven Modeling for Ex Vivo Data Analysis: Insights into Liver Transplantation and Pathobiology

Sadowsky, David and Abboud, Andrew and Cyr, Anthony and Vodovotz, Lena and Fontes, Paulo and Zamora, Ruben and Vodovotz, Yoram (2017) Dynamic Data-Driven Modeling for Ex Vivo Data Analysis: Insights into Liver Transplantation and Pathobiology. Computation, 5 (4). ISSN 2079-3197

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Extracorporeal 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.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Sadowsky, David
Abboud, Andrew
Vodovotz, Lenallv7@pitt.edullv7
Fontes, Paulo
Zamora, Rubenzamorar@pitt.eduzamorar
Vodovotz, Yoramvodovotz@pitt.eduvoovotz
Date: 23 November 2017
Date Type: Publication
Journal or Publication Title: Computation
Volume: 5
Number: 4
Publisher: MDPI AG
DOI or Unique Handle: 10.3390/computation5040046
Schools and Programs: School of Medicine > Surgery
Refereed: Yes
Uncontrolled Keywords: transplantation, extracorporeal organ perfusion, computational modeling
ISSN: 2079-3197
Official URL:
Article Type: Review
Date Deposited: 11 Jan 2021 23:17
Last Modified: 11 Jan 2021 23:17


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