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Open Access

Correction

Correction: Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome

  • Austin Chou,
  • Abel Torres-Espin,
  • Nikos Kyritsis,
  • J. Russell Huie,
  • Sarah Khatry,
  • Jeremy Funk,
  • Jennifer Hay,
  • Andrew Lofgreen,
  • Rajiv Shah,
  • Chandler McCann,
  • Lisa U. Pascual,
  • Edilberto Amorim,
  • Philip R. Weinstein,
  • Geoffrey T. Manley,
  • Sanjay S. Dhall,
  • Jonathan Z. Pan,
  • Jacqueline C. Bresnahan,
  • Michael S. Beattie,
  • William D. Whetstone,
  • Adam R. Ferguson,
  •  [ ... ],
  • the TRACK-SCI Investigators
  • [ view all ]
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An additional affiliation is missing for author Adam R. Ferguson, who is also affiliated with San Francisco Veterans Affairs Healthcare System, San Francisco, California, United States of America.

The following information is missing from the Data Availability statement: Source data has been deposited to the Open Data Commons for Spinal Cord Injury (odc-sci.org;RRID:SCR_016673) under the accession number ODC-SCI:727 (http://doi.org/10.34945/F5KG6Z).

Reference

  1. 1. Chou A, Torres-Espin A, Kyritsis N, Huie JR, Khatry S, Funk J, et al. (2022) Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome. PloS ONE, 17(4): e0265254. https://doi.org/10.1371/journal.pone.0265254 pmid:35390006

Citation: Chou A, Torres-Espin A, Kyritsis N, Huie JR, Khatry S, Funk J, et al. (2023) Correction: Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome. PLoS ONE 18(11): e0294081. https://doi.org/10.1371/journal.pone.0294081

Published: November 2, 2023

Copyright: © 2023 Chou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.