The majority of medical students believe that artificial intelligence (AI) will soon diminish the need for radiologists, and some are deterred from pursuing the specialty because of the constant insurgence of AI advancements.
The use of AI in medical imaging is growing rapidly. It has become a normalized facet in the specialty, so much so that the Food and Drug Administration (FDA) and the American College of Radiology are working together to develop interoperable regulations for the future safety of AI medical imaging algorithms. Although AI makes image reading a more efficient and possibly more accurate process, these qualities pose a real threat to the practice of image interpretation by actual radiologists.
In a study recently published in Academic Radiology, researchers from Vancouver General Hospital’s department of radiology sent out an anonymous survey to 17 Canadian medical schools with questions on how students perceived radiology and how they viewed the specialty in terms of its relationship to AI. Around 320 students responded to the survey, and out of that number, 70 students said radiology was their top specialty choice, and 133 said it was in their top three choices. Approximately 67 percent said that they believed AI would “reduce the demand for radiologists.” Even among those who said that radiology was their first choice, 48.6 percent indicated that “AI caused anxiety when considering the radiology specialty.” For about 16 percent of students, radiology would have been their first choice if AI wasn’t such an anxiety-provoking factor. Nearly 30 percent of students believed that AI “would replace radiologists in the foreseeable future.”
However, students are not entirely pessimistic about AI’s influence on radiology. According to the study’s authors, “It is important to note that, despite significant anxiety about the uncertain impact of AI, respondents overwhelmingly supported the notion of collaborating with the IT industry to facilitate the development and application of AI in radiology for AI's potential value to improve patient care.”