Abstract
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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Acknowledgments
The authors would like to thank the generous help and support from the Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.
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Conflict of Interest Statement
The authors declare that there are no conflicts of interest relevant to this article.
This study was supported by the National Natural Science Foundation of China (No. 81974355 and No. 82172525).
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Liu, Pr., Zhang, Jy., Xue, Md. et al. Artificial Intelligence to Diagnose Tibial Plateau Fractures: An Intelligent Assistant for Orthopedic Physicians. CURR MED SCI 41, 1158–1164 (2021). https://doi.org/10.1007/s11596-021-2501-4
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DOI: https://doi.org/10.1007/s11596-021-2501-4