Machine learning-based prediction of out-of-hospital births in prehospital emergency care

Key Points

• The aim is to develop machine learning models to predict out-of-hospital births using EMS data.
• Utilized routine EMS data to train machine learning models.
• Evaluated the internal predictive performance of these models.
• Analyzed decision patterns for clinical relevance.
• Models showed high predictive performance for identifying potential out-of-hospital births.
• Decision-making patterns were aligned with clinical intuition.