Classification of Recurrence Status After Surgical Treatment of Chronic Subdural Hemorrhage - A Machine Learning Approach
Despite employing rigorous machine learning methods on a large cohort of chronic subdural hematoma patients, this study concludes that routinely available clinical and radiographic variables lack sufficient predictive power to enable clinically actionable risk stratification for surgical recurrence, thereby supporting the maintenance of uniform or symptom-driven surveillance protocols rather than risk-based approaches.