【摘 要】
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Objective:To explore a new artificial intelligence(AI)-aided method to assist the clinical diagnosis of tibial plateau fractures(TPFs)and further measure its validity and feasibility.Methods:A total of 542 X-rays of TPFs were collected as a reference data
【机 构】
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Department of Orthopedics,Union Hospital,Tongji Medical College,Huazhong University of Science and T
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Objective:To explore a new artificial intelligence(AI)-aided method to assist the clinical diagnosis of tibial plateau fractures(TPFs)and further measure its validity and feasibility.Methods:A total of 542 X-rays of TPFs were collected as a reference database.An AI algorithm(RetinaNet)was trained to analyze and detect TPF on the X-rays.The ability of the AI algorithm was determined by indexes such as detection accuracy and time taken for analysis.The algorithm performance was also compared with orthopedic physicians.Results:The AI algorithm showed a detection accuracy of 0.91 for the identification of TPF,which was similar to the performance of orthopedic physicians(0.92±0.03).The average time spent for analysis of the AI was 0.56 s,which was 16 times faster than human performance(8.44±3.26 s).Conclusion:The AI algorithm is a valid and efficient method for the clinical diagnosis of TPF.It can be a useful assistant for orthopedic physicians,which largely promotes clinical workflow and further guarantees the health and security of patients.
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