Machine learning-driven identification of novel patient factors for prediction of major complications after posterior cervical spinal fusion

ConclusionWe report an ensemble ML model for prediction of major complications and readmission after posterior cervical fusion with a modest risk prediction advantage compared to LR and benchmark ML models. Notably, the features most important to the ensemble are markedly different from those for LR, suggesting that advanced ML methods may identify novel prognostic factors for adverse outcomes after posterior cervical fusion.
Source: European Spine Journal - Category: Orthopaedics Source Type: research