Clinical prediction for surgical versus nonsurgical interventions in patients with vertebral osteomyelitis and discitis.

The XGBoost model reliably predicts the indication for surgical intervention based on several readily available patient demographic information and clinical features. The interpretability of a supervised ML model provides robust insight into patient outcomes. Furthermore, it paves the way for the development of an efficient hospital resource allocation instrument, designed to guide clinical suggestions.