Topological network analysis of patient similarity for precision management of acute blood pressure in spinal cord injury

Topological network analysis of patient similarity for precision management of acute blood pressure in spinal cord injury

Background: Predicting neurological recovery after spinal cord injury (SCI) is challenging. Using topological data analysis, we have previously shown that mean arterial pressure (MAP) during SCI surgery predicts long-term functional recovery in rodent models, motivating the present multicenter study...

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Auteurs principaux: Abel Torres-Espín, Jenny Haefeli, Reza Ehsanian, Dolores Torres, Carlos A Almeida, J Russell Huie, Austin Chou, Dmitriy Morozov, Nicole Sanderson, Benjamin Dirlikov, Catherine G Suen, Jessica L Nielson, Nikos Kyritsis, Debra D Hemmerle, Jason F Talbott, Geoffrey T Manley, Sanjay S Dhall, William D Whetstone, Jacqueline C Bresnahan, Michael S Beattie, Stephen L McKenna, Jonathan Z Pan, Adam R Ferguson, The TRACK-SCI Investigators
Format: article
Langue:EN
Publié: eLife Sciences Publications Ltd 2021
Sujets:
topological networks analysis
spinal cord injury
blood pressure
machine learning
surgery
Medicine
R
Science
Q
Biology (General)
QH301-705.5
Accès en ligne:https://doaj.org/article/deaeee6d6a7c4743a5ba3373d4ca53da
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https://doaj.org/article/deaeee6d6a7c4743a5ba3373d4ca53da

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