RESUMO
Thyroid diseases are diverse, ranging from benign conditions to potentially life-threatening disorders. Recently, the application of artificial intelligence (AI) in evaluating thyroid disease has significantly enhanced medical research, diagnosis prediction, and algorithm development. Coupled with this advancement is the rising focus on the importance of gender equality in scientific publications. This study delves into the gender trends of first authors in papers related to "Artificial Intelligence and Thyroid" sourced from PubMed from 2003 to 2022, scrutinizing these trends based on both country and year. A bibliometric analysis was conducted on PubMed to retrieve relevant articles over this 19-year time span. Following this, the names and affiliated countries of the first authors were determined. The Namsor app, a tool for classifying personal names by gender, origin, or ethnicity, was then used to segregate the data based on gender. Statistical analyses were performed using the R software- ARIMA model and Fisher's exact test was applied to examine the correlations between gender and country of origin. From the 254 analyzed articles, 43.5% of the first authors were female, while 56.69% were male. The year 2022 saw the most significant number of female first-author publications. Intriguingly, the European Journal of Radiology was prominent due to its favorable gender ratio. Moreover, the association between gender and country was significant, with China being a standout. Limitations included focusing only on PubMed journals and using a third party for gender identification. Nevertheless, the study reveals a move toward gender parity in AI and thyroid research over the past 18 years, emphasizing the importance of sustained efforts for academic inclusivity.
