Comparison of the predictive performance of machine learning and conventional logistic regression models for poor discharge outcomes in patients with Aneurysmal subarachnoid hemorrhage: A retrospective cohort study

Key Points

• Poor discharge outcomes are predicted using machine learning and logistic regression models, revealing differences in performance.
• The analysis compares these methods to assess their predictive accuracy for patients suffering from aneurysmal subarachnoid hemorrhage.
• A retrospective cohort study evaluates the efficacy of machine learning versus traditional methods on patient outcomes.
• These findings may improve future tools for predicting risks post-aneurysmal subarachnoid hemorrhage, enhancing patient care.