Machine Learning-based Radiomic Model for Early Diagnosis of Male Urethral Injury in Pelvic Fracture Patients

Key Points

• A machine learning model significantly enhances early diagnosis of urethral injury.
• The model shows a positive diagnostic performance with a sensitivity rate exceeding 85%.
• Observational analysis utilized radiomics data from pelvic fracture cases to train the model.
• The findings highlight the potential for using machine learning in clinical diagnostics of urethral injuries.