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Dear Editor,
We appreciate the thoughtful comments on our bibliometric analysis of artificial intelligence (AI) research in foot and ankle surgery. We are pleased that our work has stimulated further discussion on this emerging topic.
First, our study was conducted following widely accepted bibliometric methodologies, using the Web of Science Core Collection as the primary data source.1,2 We fully acknowledge that database selection and citation lag may introduce potential bias, which we explicitly discussed in the Limitations section of our paper. As with most bibliometric studies, such methodological constraints are inherent and should be interpreted accordingly.
Second, we agree that clinical applications of AI in arthroscopy, ligament reconstruction, ankle fusion and rehabilitation outcomes represent promising future directions. However, current research in these areas remains scarce in the foot and ankle field. Therefore, our analysis did not identify these topics as future trends or emerging hotspots at this stage. Nevertheless, we concur that they hold substantial potential for future exploration and translation into clinical practice.
Finally, we recognize the importance of emerging paradigms such as federated learning and multimodal AI. Federated learning and multimodal AI have already begun to be applied in the field of orthopaedic, which address critical issues related to data privacy, heterogeneity, and generalizability.3,4 At present, their application in foot and ankle surgery is still limited, but we anticipate that these approaches will play an increasingly significant role in the next phase of AI-driven orthopaedic research.
We appreciate the authors’ constructive insights, which help broaden the discussion and highlight important avenues for advancing the integration of AI into orthopaedic surgery.
Sincerely,
Hui Du
On behalf of the authors