Prediction model for spinal cord injury in spinal tuberculosis patients using multiple machine learning algorithms: a multicentric study

Prediction model for spinal cord injury in spinal tuberculosis patients using multiple machine learning algorithms: a multicentric study

Abstract Spinal cord injury (SCI) is a prevalent and serious complication among patients with spinal tuberculosis (STB) that can lead to motor and sensory impairment and potentially paraplegia. This research aims to identify factors associated with SCI in STB patients and to develop a clinically sig...

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Bibliographic Details
Main Authors: Sitan Feng, Shujiang Wang, Chong Liu, Shaofeng Wu, Bin Zhang, Chunxian Lu, Chengqian Huang, Tianyou Chen, Chenxing Zhou, Jichong Zhu, Jiarui Chen, Jiang Xue, Wendi Wei, Xinli Zhan
Format: Article
Language:English
Published: Nature Portfolio 2024-04-01
Series:Scientific Reports
Subjects:
Spinal tuberculosis
Spinal cord injury
Machine learning
Predictive model
Model interpretation
Model deployment
Online Access:https://doi.org/10.1038/s41598-024-56711-0

Internet

https://doi.org/10.1038/s41598-024-56711-0

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