Deep Learning Algorithm for Abdominal Trauma Diagnosis on CT Imaging

Deep learning algorithms demonstrate high accuracy in detecting renal, liver, and spleen injuries on abdominal CT scans. With a notable performance in renal injury detection (accuracy: 0.932), the model exhibits potential for rapid preliminary screening and adjunctive diagnosis of traumatic abdominal injuries. The results suggest promising applicability in emergency settings, aiding clinicians in timely and accurate assessment of multiple organ injuries from CT imaging data.