Machine learning versus conventional grading systems for prognostication in aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis.

Machine learning models demonstrated good to excellent discrimination, with AUCs ranging from 0.81 to 0.97.

Machine learning models outperformed conventional grading systems in most studies and showed comparable performance in the remainder.

Subgroup analyses confirmed statistically significant prognostic accuracy across clinical-only, imaging-based, and multimodal machine learning models.