Cross-race vs. same-race collaboration in plastic surgery: AI-driven analysis of research and race-interaction dynamics

Background: Racial diversity in plastic surgery research remains a challenge. This study employs artificial intelligence (AI)-driven big data analysis to assess racial representation, cross-race mentorship trends, and research productivity disparities among plastic surgery authors over 12 years (2010–2022). Methods: A retrospective, cross-sectional study was conducted using AI-based web scraping to extract authorship data from 24 PubMed-indexed plastic surgery journals. RaceAPI, a machine-learning-based name-classification tool trained on U.S. Census data, inferred racial identity. Chi-square tests were used to evaluate racial disparities in first and senior authorship, mentorship patterns, and research output. Results: Among 16 019 publications, White researchers remained the dominant group among first authors (70% in 2010 vs. 66.2% in 2022, P < 0.001) and senior authors (73.8% vs. 72.6%, P < 0.01). Black first and senior authorship declined (8.1% to 6.4%, P < 0.001; 9.2% to 6.1%, P < 0.001), while Asian representation increased (first: 16% to 18.8%, P = 0.027; senior: 11.7% to 16%, P < 0.001). White authors had significantly higher research productivity (2.15 papers per author) than Asian (1.97), Black (1.76), and Hispanic (1.68) researchers ( P < 0.05). Black senior authors had the highest rate of cross-race mentorship (77.5%), while White (26.8%) and Asian (27.3%) senior authors exhibited strong same-race mentorship preferences. Conclusions: Persistent racial disparities in authorship and research participation among racial groups that are persistently underrepresented in medical school and plastic surgery residencies suggest the need to assess and address educational barriers prior to medical school. Strengthening mentorship networks and increasing access to research for minority trainees could foster a thriving plastic surgery workforce for all communities, including those currently underserved. Level of Evidence: Level III, cross-sectional study.

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Journal
Annals of Medicine and Surgery
Published
2026-07-27
DOI
https://doi.org/10.1097/ms9.0000000000005344
Primary Topic
Diversity and Career in Medicine
Type
article
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article

Cross-race vs. same-race collaboration in plastic surgery: AI-driven analysis of research and race-interaction dynamics

Sofoklis Goulas, Gregory A. Lamaris, Georgios Karamitros, Michael P. Grant et al.
Annals of Medicine and Surgery
Diversity and Career in Medicine
article

Cross-race vs. same-race collaboration in plastic surgery: AI-driven analysis of research and race-interaction dynamics

Sofoklis Goulas, Gregory A. Lamaris, Georgios Karamitros, Michael P. Grant, Heather J. Furnas
article en

Abstract

Background: Racial diversity in plastic surgery research remains a challenge. This study employs artificial intelligence (AI)-driven big data analysis to assess racial representation, cross-race mentorship trends, and research productivity disparities among plastic surgery authors over 12 years (2010–2022). Methods: A retrospective, cross-sectional study was conducted using AI-based web scraping to extract authorship data from 24 PubMed-indexed plastic surgery journals. RaceAPI, a machine-learning-based name-classification tool trained on U.S. Census data, inferred racial identity. Chi-square tests were used to evaluate racial disparities in first and senior authorship, mentorship patterns, and research output. Results: Among 16 019 publications, White researchers remained the dominant group among first authors (70% in 2010 vs. 66.2% in 2022, P < 0.001) and senior authors (73.8% vs. 72.6%, P < 0.01). Black first and senior authorship declined (8.1% to 6.4%, P < 0.001; 9.2% to 6.1%, P < 0.001), while Asian representation increased (first: 16% to 18.8%, P = 0.027; senior: 11.7% to 16%, P < 0.001). White authors had significantly higher research productivity (2.15 papers per author) than Asian (1.97), Black (1.76), and Hispanic (1.68) researchers ( P < 0.05). Black senior authors had the highest rate of cross-race mentorship (77.5%), while White (26.8%) and Asian (27.3%) senior authors exhibited strong same-race mentorship preferences. Conclusions: Persistent racial disparities in authorship and research participation among racial groups that are persistently underrepresented in medical school and plastic surgery residencies suggest the need to assess and address educational barriers prior to medical school. Strengthening mentorship networks and increasing access to research for minority trainees could foster a thriving plastic surgery workforce for all communities, including those currently underserved. Level of Evidence: Level III, cross-sectional study.

Annals of Medicine and Surgery
Brookings Institution (US), University of Maryland, Baltimore (US), University of Maryland Medical Center (US), Vanderbilt University Medical Center (US), Stanford University (US)
Openalex Percentile: Top 4%
Diversity and Career in Medicine
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