Majority of radiology residents support implementation of AI-based curriculum
Implementing materials on artificial intelligence into curriculum during residency can help better prepare future radiologists for the use of AI in clinical settings.
This was concluded after radiology residents were surveyed on their experiences with a similar introduction into artificial intelligence-based decision support systems (AI-DSS) in clinical settings at the University of Massachusetts Chan Medical School. Residents who were given access to the AI-DSS reported feeling that the tool was useful in multiple clinical scenarios, and its use was overwhelmingly supported by those who provided feedback [1].
Considering how recent data has indicated that a significant portion of medical students feel that AI will eventually deem radiologists obsolete, the positive feedback from residents who were introduced to the curriculum is encouraging, authors of the new paper published in Clinical Imaging suggested.
“Regardless of whether AI is a threat or opportunity to radiology, the undeniable truth is that AI will revolutionize radiology and radiologists will be responsible for managing radiology AI systems,” corresponding author Tina Shiang, from the University of Massachusetts Chan Medical School, and colleagues wrote.
Out of the residents who were surveyed, 91% supported incorporating AI-based materials into curriculum. The system was particularly useful in triage and troubleshooting settings according to 83.3% and 66.7% of respondents, although they were less enthusiastic about its role in increasing their speed and accuracy.
The majority (83.3%) shared that their outlook on the future of AI in radiology was positive, but the respondents were divided on when its introduction should begin in residency. Some cited concerns about introducing the curriculum too soon, stating that they felt like it could make junior radiologists become “dependent” on its use, while others believed that introducing it earlier in residency would encourage familiarity with software that will inevitably play a role in clinical workflows.
Encouragingly, only a very small portion of respondents (8.3%) harbored any concern for AI limiting their job prospects. This is in contrast to some recent analyses that found patterns of hesitance to pursue radiology due to concerns about AI’s future role in radiology.
“We hope our experience will provide incentive and guidance for other institutions to establish an AI program for their trainees,” the authors concluded.
More data from the survey can be found here.