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Gender Authorship Among Urology Artificial Intelligence Publications: A 10-Year Retrospective Analysis
Gillian Murray1, Ranveer M S Vasdev1, Luqman Ellythy2
1Department of Urology, Mayo Clinic, Rochester, MN.
Urology
|May 2, 2025
Summary
Gender disparities exist in urology artificial intelligence (AI) research authorship. Female representation is lower, particularly in specialized journals, impacting publication metrics.
Area of Science:
- Urology
- Artificial Intelligence
- Medical Informatics
- Gender Studies
Background:
- The increasing integration of artificial intelligence (AI) in urology necessitates an examination of authorship demographics.
- Understanding gender representation in AI research is crucial for promoting equity and diversity in scientific fields.
Purpose of the Study:
- To characterize gender authorship patterns in urology-related artificial intelligence (AI) research.
- To identify potential gender-based disparities in author representation and publication impact within this specialized field.
Main Methods:
- Retrospective review of 799 urology-related AI research articles published between 2014 and 2024.
- Utilized MEDLINE, Embase, and Web of Science databases for comprehensive literature retrieval.
- Estimated first and senior author gender using Gender API© for demographic analysis.
Main Results:
- Female authors constituted 17.6% of first authors and 12.5% of senior authors in urology AI research.
- A statistically significant lower proportion of female authors was observed in urology-specific journals compared to males (P < .05).
- Publication impact factor was significantly lower for articles with female senior authors (P < .05).
Conclusions:
- Significant gender disparities are evident in urology-related AI research authorship.
- Lower representation and impact factor for female authors highlight the need for targeted interventions.
- Future research should focus on strategies to enhance female participation and address existing inequities in the field.
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