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Related Experiment Video

Updated: Jun 5, 2026

Automated Gait Analysis to Assess Functional Recovery in Rodents with Peripheral Nerve or Spinal Cord Contusion Injury
06:31

Automated Gait Analysis to Assess Functional Recovery in Rodents with Peripheral Nerve or Spinal Cord Contusion Injury

Published on: October 6, 2020

Machine Learning-Based Prediction of Independent Ambulation Following Intramedullary Spinal Cord Tumor Resection.

Blake Perdikis1, Adhith Palla1, Nicolas K Goff1,2

  • 1Department of Neurosurgery, NYU Langone Health, New York, New York, USA.

Neurosurgery
|June 4, 2026
PubMed
Summary

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Machine learning models accurately predict independent ambulation after intramedullary spinal cord tumor (IMSCT) resection. Enhanced granular data modeling significantly improves prognostication, aiding patient counseling.

Area of Science:

  • Neurosurgery
  • Machine Learning
  • Spinal Cord Oncology

Background:

  • Intramedullary spinal cord tumor (IMSCT) resection poses significant risks of postoperative neurological deficits.
  • Current prognostication methods for neurological recovery after IMSCT resection are limited.

Purpose of the Study:

  • To develop and evaluate machine learning models for predicting independent ambulation after IMSCT resection.
  • To assess the impact of granular recovery data on prognostication accuracy.

Main Methods:

  • Retrospective review of adult IMSCT resections (March 2009 - August 2025).
  • Extracted demographic, oncologic, and perioperative data, including American Spinal Injury Association Impairment Scale (AIS) and Modified McCormick Scale (MMCS) grading.
  • Developed four machine learning models, with independent ambulation as the primary outcome, evaluated using area under the receiver operating characteristic curve (AUROC).
Keywords:
AmbulationIMSCTIntramedullaryMachine learningSpinal tumors

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Determining the Functional Status of the Corticospinal Tract Within One Week of Stroke

Published on: February 22, 2020

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Last Updated: Jun 5, 2026

Automated Gait Analysis to Assess Functional Recovery in Rodents with Peripheral Nerve or Spinal Cord Contusion Injury
06:31

Automated Gait Analysis to Assess Functional Recovery in Rodents with Peripheral Nerve or Spinal Cord Contusion Injury

Published on: October 6, 2020

Determining the Functional Status of the Corticospinal Tract Within One Week of Stroke
09:10

Determining the Functional Status of the Corticospinal Tract Within One Week of Stroke

Published on: February 22, 2020

Main Results:

  • Fifty-four patients underwent 55 IMSCT resections; encapsulated tumors were more likely to achieve gross total resection.
  • By 4 weeks postoperatively, MMCS conversion correlated with ambulatory conversion; by 6 months, both AIS and MMCS conversion correlated significantly.
  • The comprehensive granular model achieved an AUROC of 0.833 at 4 weeks and 1.00 at 6 months for predicting ambulation, outperforming individual clinical scales.

Conclusions:

  • Postoperative neurological recovery following IMSCT resection stabilizes by 6 months.
  • Enhanced granularity of recovery data improves the accuracy of predicting independent ambulation.
  • Accurate ambulation modeling can significantly enhance patient counseling for IMSCT.