Female Authorship Trends Among Articles About Artificial Intelligence in North American Radiology Journals. Issue 2 (May 2023)

• Record Type: Journal Article
• Authors: Yan, Tyler D.; Yuan, Po Hsiang (Shawn); Saha, Tania; Lebel, Kiana; Spalluto, Lucy; Yong-Hing, Charlotte J.
• Is Part Of: Canadian Association of Radiologists journal. Volume 74:Issue 2(2023)
• Page Start: 264
• Page End: 271
• Publication Date: 2023-05
• Subjects: artificial intelligence -- radiology -- gender -- inclusivity -- diversity; Radiology, Medical -- Periodicals; Radiology, Medical -- Canada -- Periodicals; 616.0757
• DOI: 10.1177/08465371221122637
• Languages: English
• ISSNs: 0846-5371

Abstract

Purpose: To examine trends in female authorship of peer-reviewed North American radiology articles centred around artificial intelligence (AI).Method: A bibliographic search was conducted for all AI-related articles published in four North American radiology journals. Collected data included the genders of the first and last (senior) authors, year and country. We compared the trends of female authorship using Pearson chi-square, Fisher exact tests and logistic regression models.Results: 453 articles met the inclusion criteria. Among these, 107 (22.3%) had a female first author and 97 (27.3%) had a female senior author. Female first authors were over three times more likely to publish with a female senior author. Among the four journals, the CARJ had the highest proportion of female senior authors at 45.5%. The only significant temporal trend identified was an increase over the years in female senior authors in Radiology. Twenty-four countries contributed to the included articles, with the largest contributors being the United States (n = 290) and Canada (n = 30). Of the countries contributing more than 15 articles, there were none with above 50% female authorship.Conclusions: Female authors are underrepresented in AI-related radiology literature. However, there has been an encouraging recent increase in female authorship in AI-related radiology articles trending towards significance. There is a great opportunity to improve female representation in AI with intentional mentorship and recruitment. We urge more platforms for female voices in radiology as AI becomes increasingly integrated into the radiology community.