LAUSR

PURPOSE Rapid advances in artificial intelligence (AI) have generated significant interest in the radiology community. However, formal AI initiatives and leadership roles in academic radiology has not been formally evaluated. The purpose of this study was to assess the prevalence of formal AI initiatives and leadership roles in academic radiology departments. METHODS Radiology departments with National Institutes of Health funding in fiscal year 2019 were identified. AI educational and research initiatives, leadership roles, and industry partnerships were assessed by searching department websites for AI-related keywords. Correlations between NIH funding and the presence of AI initiatives were evaluated with linear regression. RESULTS Sixty-two radiology departments with NIH funding were included in this study. Educational initiatives on AI were offered by 29 (47%) departments. Fifty-five (89%) departments had at least 1 AI researcher and 34 (55%) departments were affiliated with an AI research laboratory, center, or cluster. AI-specific leadership roles and industry partnerships were identified in 3 (5%) and 23 (37%) departments, respectively. The amount of NIH funding did not have a significant linear correlation with educational initiatives (P = 0.08) but there was a significant linear correlation between funding and presence of research initiatives (P = 0.003). CONCLUSIONS AI educational initiatives were offered by almost half of radiology departments. Most departments had AI researchers and affiliated labs, but the majority were not led by the radiology department, and few had formal AI leadership roles. In the new AI era, these findings provide a benchmark for departments considering implementing formal AI initiatives.