Fig. 6 | Scientific Reports

Fig. 6

From: Constructing a nomogram for short-term prognosis in postoperative patients with aneurysmal subarachnoid hemorrhage: a two-center retrospective study

Fig. 6

Machine learning model results. Data 6 A Random Forest Feature Importance: Hydrocephalus (41.6%). GCS (23%). Hunthess (15.9%). Hypertension (9.7%). WBC (3.5%). MLR (3.5%). Position (2.2%). Side (0.6%). Data 6 B Gradient Boosting Feature Importance: Hydrocephalus (39.4%). GCS (27.4%). WBC (10.5%). MLR (10%). Hunthess (5.6%). Hypertension (4.6%). Side (1.5%). Position (1.1%).

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