人工智能在胸部骨折 CT诊断中的应用.

Objective To investigate the diagnostic performance and application value of an artificial intelligence (AI) bone disease diagnosis system in the diagnosis of thoracic fractures. Methods A retrospective analysis was performed on 726 cases of thoracic fractures confirmed by chest CT re-examination 3-6 weeks after trauma emergency admission at Shenzhen University General Hospital. The recall rate, precision rate, and F1 score of AI, two radiologists, and the radiologists assisted by AI in diagnosing thoracic fractures were calculated.Results The recall rate and F1 score of AI in detecting rib fractures were 0.91 and 0.92, respectively, both higher than those of Radiologist 1 (0.77, 0.85) and Radiologist 2 (0.84, 0.90). The precision rate of AI (0.92) was lower than that of Radiologist 1 (0.95) and Radiologist 2 (0.96). With AI assistance, the recall rate, precision rate, and F1 score of Radiologist 1 and Radiologist 2 in detecting rib fractures were 0.94, 0.95, 0.94 and 0.97, 0.98, 0.97, respectively. For detecting other thoracic fractures, the recall rate and F1 score of AI (0.90, 0.90) were higher than those of Radiologist 1 (0.62, 0.74) and Radiologist 2 (0.73, 0.81). With AI assistance, the recall rate, precision rate, and F1 score of Radiologist 1 and Radiologist 2 in detecting other thoracic fractures were 0.94, 0.95, 0.94 and 0.97, 0.97, 0.97, respectively. Conclusion AI can efficiently and sensitively detect thoracic fractures in chest CT scans of emergency trauma patients, potentially optimizing the diagnosis and treatment process for emergency trauma patients. [ABSTRACT FROM AUTHOR]