Lack of AI education in diagnostic radiology may be scaring off trainees
According to survey results recently published online in the Journal of the American College of Radiology, more than one-third of radiologists lack exposure to artificial intelligence (AI) educational material and resources. Additionally, most trainees' desire to learn about or pursue diagnostic radiology is hindered by AI's role in medicine.
"There is a need to develop educational resources to help radiologists assume an active role in guiding and facilitating the development and implementation of artificial intelligence tools in diagnostic radiology," said lead author Fernando Collado-Mesa, MD, radiologist at the University of Miami Miller School of Medicine, and colleagues.
An anonymous, online multiple-choice questionnaire was distributed and returned by 66 percent of 104 attending radiologists and trainees at a single diagnostic radiology residency program. The response rate for trainees was 63 percent (34 of 54) and 70 percent (35 of 50) for attending radiologists who had an average of 12 years in practice and a majority specializing in neuroradiology or abdominal radiology.
Results from the survey revealed that 29 percent of respondents, both attending radiologists and trainees, use AI tools in their daily work. However, only trainees expressed doubts about whether they would have pursued diagnostic radiology had they known about AI's future impact on radiology. Still, they want to learn more about it, according to study results. Additionally, a small number of trainees expressed concern that jobs will disappear because of AI and machine learning.
Although the survey revealed a strong need to promote AI and machine learning resources to radiologists, a willingness to collaborate with the development of AI and machine learning tools in the specialties of attending radiologists and trainees is encouraging.
"Despite some predictions that AI and machine learning could eventually replace them, most attending radiologists and trainees at our residency training program are willing to collaborate with the development of AI and machine learning tools to be used in their specialty," the researchers concluded.
A recent graduate from Dominican University (IL) with a bachelor’s in journalism, Melissa joined TriMed’s Chicago team in 2017 covering all aspects of health imaging. She’s a fan of singing and playing guitar, elephants, a good cup of tea, and her golden retriever Cooper.