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This paper is in the following e-collection/theme issue:

Reviews in AI (39) Decision Support for Health Professionals (1677) Machine Learning (2289) Spinal Cord Injury Rehabilitation (91) Artificial Intelligence (2434) Applications of AI (371)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66233, first published .
Predicting Spinal Cord Injury Prognosis Using Machine Learning: Systematic Review and Meta-Analysis

Predicting Spinal Cord Injury Prognosis Using Machine Learning: Systematic Review and Meta-Analysis

Predicting Spinal Cord Injury Prognosis Using Machine Learning: Systematic Review and Meta-Analysis

Authors of this article:

Linxing Zhong1 Author Orcid Image ;   Qiying Huang1 Author Orcid Image ;   Hao Zhang1 Author Orcid Image ;   Liang Xue1 Author Orcid Image ;   Yehuang Chen1 Author Orcid Image ;   Jianwu Wu1 Author Orcid Image ;   Liangfeng Wei1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Andrabi S, Steinmetz M, Labhasetwar V. Evolving role of biomarkers in spinal cord injury: From research to clinical translation. Biomedicine & Pharmacotherapy 2026;199:119389 View
  2. Perez-Sanpablo A, Rodriguez-Barragan M, Meneses-Pañaloza A, Quinzanos Fresnedo J, Barrera-Ortiz A, Palomino-Ramos F, Prado-Escobar O, Rodriguez-Urrea M, Lopez-Nava I, Ambrosio-Bastian J. Machine Learning-Based Predictive Model for Functional Independence in Spinal Cord Injury: Protocol for a Predictive Rule Development and Validation Study (Preprint). JMIR Research Protocols 2026 View