As a follow-up to part one of this international survey on artificial intelligence (AI), which surveyed over 1,000 radiologists and radiology residents and explored early adoption of AI, as well as radiologists’ perspectives on and fear of being replaced by these technologies, part 2 discusses the expectations of AI and the hurdles associated with implementation and education.
Regardless of the particular views of the study participants regarding AI, the survey resulted in a majority (82%) of participants expecting AI to have a significant impact on radiology within the next ten years, and incorporation of AI into radiology education and curricula (e.g. data management, ethical and legal issues, etc.) may be the best approach going forward.
Read part 2 of this study in its entirety in the link below.
Key points
- There is broad demand from the radiological community to incorporate AI into residency programs, but there is less support to recognize imaging informatics as a radiological subspecialty.
- Ethical and legal issues and lack of knowledge are recognized as major bottlenecks for AI implementation by the radiological community, while the shortage in labeled data and IT-infrastructure issues are less often recognized as hurdles.
- Integrating AI education in radiology curricula including technical aspects of data management, risk of bias, and ethical and legal issues may aid successful integration of AI into diagnostic radiology.
Authors: Merel Huisman, Erik Ranschaert, William Parker, Domenico Mastrodicasa, Martin Koci, Daniel Pinto de Santos, Francesca Coppola, Sergey Morozov, Marc Zins, Cedric Bohyn, Ural Koç, Jie Wu, Satyam Veean, Dominik Fleischmann, Tim Leiner & Martin J. Willemink
