Predicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning.

ABSTRACT:

Introduction

This study aimed to develop machine learning models to predict neurological outcomes in patients with degenerative cervical myelopathy (DCM) after surgical decompression and identify key factors that contribute to a better outcome, providing a reference for patient consultation and surgical decision-making.

Methods

This retrospective study reviewed 1,895 patients who underwent cervical decompression surgery for DCM at Peking University Third Hospital from 2011 to 2020, with 672 patients included in the final analysis. Five machine learning methods, namely, linear regression (LR), support vector machines (SVM), random forest (RF), XGBoost, and Light Gradient Boosting Machine (LightGBM), were used to predict whether patients achieved the minimal clinically importa

SUBMITTER: Zhou S 

PROVIDER: S-EPMC11913819 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature