Authorship gender among articles about artificial intelligence in breast imaging.

ABSTRACT

RATIONALE AND OBJECTIVES: The purpose of this study is to investigate the variance of women authors, specifically first and senior authorship among peer-reviewed artificial intelligence-related articles with a specific focus in breast imaging. MATERIALS AND METHODS: A strategic search was conducted in July 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to capture all existing and publicly available peer-reviewed articles intersecting AI and breast imaging. Primary outcomes were first and senior authors' gender, which were assigned with the aid of an emailed self-declaration survey. Secondary outcomes included country of article, journal impact factor, and year of publication. Comparisons were made using logistic regression models and analysis of variances. RESULTS: 115 studies were included in the analysis. Women authors represented 35.7% (41/115) and 37.4% (43/115) of first and senior authors, respectively. Logistic regression modelling showed a significant increase in women senior authors over time but no changes in women first authors. Impact factor was not associated with female authorship and certain countries had women authorship reach over 50%. CONCLUSION: This study demonstrates that there is a significant authorship gender gap in artificial intelligence breast imaging research. An increasing temporal trend of senior authors in breast imaging AI-related research is a promising prognosis for more women voices in this field. Further study needs to be done to understand the reasons behind this gap and any potential implications.