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Artificial Intelligence in Plastic and Reconstructive Surgery: A Bibliometric Study of the 50 Most-cited Articles
Pharel Njessi1,2, Olivier Camuzard1, Elise Lupon1,2
1From the Department of Plastic and Reconstructive Surgery, Institut Universitaire Locomoteur et du Sport, Pasteur 2 Hospital, University Côte d'Azur, Nice, France.
Background:
Artificial intelligence (AI) has gained increasing attention in the surgical literature, including plastic and reconstructive surgery (PRS). However, the characteristics and trends of the most influential publications on AI in PRS remain poorly defined.
Methods:
The online Web of Science Core Collection was searched on November 18, 2025, to identify articles on AI applications in PRS. Title, authorship information, publication year, journal, funding, and citation count were recorded. Studies were further classified based on application domain and PRS subspecialty.
Results:
The 50 most-cited articles on AI in PRS were published between 2001 and 2024, with citation counts ranging from 45 to 124. Most articles originated from the United States (n = 18; 1166 citations) and were published by plastic surgeons (n = 17; 1332 citations). Imaging assessment (n = 21; 1564 citations) represented the most common application of AI, whereas the predominant PRS subspecialty was craniofacial surgery (n = 32; 2364 citations).
Conclusions:
This bibliometric analysis highlights the most influential publications and emerging applications of AI in plastic surgery, revealing that image-based approaches predominate, particularly in craniofacial surgery, whereas adoption remains uneven across PRS subspecialties. These findings underscore current research priorities and identify areas where AI development remains limited, offering a foundation to guide future work in this rapidly evolving field.
