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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Autores principales:	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
Formato:	article
Lenguaje:	EN
Publicado:	eLife Sciences Publications Ltd 2021
Materias:	topological networks analysis spinal cord injury blood pressure machine learning surgery Medicine R Science Q Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/deaeee6d6a7c4743a5ba3373d4ca53da
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Topological network analysis of patient similarity for precision management of acute blood pressure in spinal cord injury

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