Altmetric Analysis of Artificial Intelligence Articles in Plastic Surgery

Abstract

OBJECTIVE Our objective was to identify the social impact factor of plastic surgery papers in the AI space. METHODS All fields in the Web of Science database were searched with descriptive terms and Boolean operators to identify articles relevant to plastic surgery and AI. 141 articles were analyzed. Altmetric Attention Score (AAS), a measure of the social dissemination of an article, was determined using Altmetric explorer. Articles were ranked by AAS and citation count, and their characteristics were analyzed by the Pearson correlation coefficient, Mann-Whitney U test, Kruskal-Wallis test, and Fisher exact test, where appropriate. RESULTS The mean AAS of the 50 most disseminated articles online was 11.3 ± 19.2, primarily driven by mentions on Twitter (12.2 ± 16.5). All articles were published in 2014 or later, with 68% published between 2020 and 2022. A majority of articles (64%) were multi-institutional collaborations and 34% were multi-national collaborations. The most common subspecialty of social interest was craniofacial/pediatric surgery (22%). First authors were predominantly male (84%) and from the United States (54%). DISCUSSION AI has significant potential in the field of plastic surgery. Overall, there remains much to be discovered based on the current dearth in literature, suggesting further work remains.

Ähnliche Arbeiten