Prediction of cervical spine injury in young pediatric patients: an optimal trees artificial intelligence approach

Machine learning model using Optimal Classification Trees predicts cervical spine injury in children under 3 years with 93.3% sensitivity based on Glasgow Coma Score and age. The approach reduces unnecessary CT imaging and associated radiation risks while maintaining high diagnostic accuracy in non-verbal pediatric trauma patients.