Interpretable Deep Learning Model for Pediatric Strangulated Small Bowel Obstruction on CT: A Multicenter Study

To develop and validate a deep learning-based multi-instance learning model that integrates CT imaging and clinical data to improve the accuracy of discriminating between strangulated small bowel obstruction (StSBO) from simple small bowel obstruction (SiSBO) in pediatric patients.