26 September 2024 : Database Analysis
Development and Internal Validation of Machine Learning to Predict Postoperative Worse Functional Status after Surgical Treatment for Thoracic Spinal Stenosis
Tun Liu12ABCE, Jia Li2D, Huaguang Qi3F, Bin Guo2B, Songchuan Zhao4CD, Baoping Zhang2F, Langbo Li5D, Gang Wu2A, Gang Wang1D*DOI: 10.12659/MSM.945310
Med Sci Monit 2024; 30:e945310
Figure 2 Feature importance plots for machine learning (ML) models included pre- and intra- variables to predict postoperative worse functional status. Using (A) XGBoost 30-day after surgery and (B) Naïve Bayes 6 months after surgery. The top 10 important features are listed in descending order. The y axis represents the important features listed in the descending order. The x axis stands for the relative importance of each variable in developing postoperative worse functional status. ML – machine learning; SSEP – somatosensory evoked potential; MEP – motor evoked potential; JOA – Japanese Orthopedic Association.