Machine learning-based models using preoperative imaging and clinical data to predict intraoperative rebleeding and functional recovery in intracerebral hemorrhage patients: a multicenter study

Key Points

• To develop and validate machine learning models that predict intraoperative rebleeding and functional recovery in patients with intracerebral hemorrhage.
• Utilized preoperative imaging and clinical data for model training.
• Validated models across multiple hospital centers.
• Applied machine learning techniques for accurate risk assessments.
• Models accurately predicted intraoperative rebleeding risk.
• Predictions correlated with postoperative functional recovery outcomes.
• Potential to guide individualized treatment approaches for patients.