5 reasons radiologists should feel confident about learning—and teaching—AI
For years now, radiology educators have been reassuring prospects, recruits and trainees that artificial intelligence can only—and will only—assist or augment radiologists. And still a nervous concern continues to come up:
Is AI going to replace radiology?
A medical student at the University of British Columbia posed precisely that question earlier this year during the curriculum’s first radiology lecture. Other students soon chimed in with similar misgivings despite the instructing radiologist’s wise tutelage.
Upon hearing of the episode, a handful of UBC professors felt motivated to flesh out a response in writing. The result is an opinion piece published this month in the Canadian Association of Radiologists Journal [1].
“This experience highlighted a knowledge gap that must be addressed in order to prepare medical students for a future where they will inevitably be working with AI,” radiologist Kathryn Darras, MD, and colleagues write.
The need is real, the authors suggest, to remedy the dearth of formal AI education in most medical schools. Efforts must be made, they urge, “to clarify the evolving role of AI in patient care and to address students’ misconceptions.”
To nudge radiology educators, mentors and informal advisers toward taking up that mantle, Darras and co-authors hit on five reasons for optimism in the specialty-wide project:
1. Radiologists may be the best physicians to address the AI knowledge gap at the medical student level. Radiologists regularly embrace new technologies, in the process championing change and collaborating with multidisciplinary teams, the authors point out. Consequently, “radiologists are the most likely clinicians to be early adopters of AI and also the best situated to share their knowledge and experience with learners.”
2. Over the next decades in radiology, AI will expand to increase our accuracy, enhance our clinical decision-making algorithms, and aid in advanced post-processing of imaging data. In clinical settings, machine learning systems improve care quality and increase patient access while easing radiologists’ workloads, Darras and colleagues underscore. For example, AI systems “protect patients by ensuring that the vertebral segments are counted correctly on cross-sectional imaging or that all areas of the breast are examined on a mammogram.”
3. Radiologists are the champions of technological change in medicine. As such they owe it to all of healthcare to “seize the opportunity to shift this conversation and educate the public about the true state of AI and its benefits to patient care,” the authors assert. Toward that end, radiologists “must educate themselves, translate their knowledge to their trainees and translate the role of AI to patients.”
4. Physicians will not be expected to design or code new tools for AI systems or to understand the mathematics behind the algorithms. Radiologists will, however, “need to understand certain core principles of AI, such as machine learning and deep learning, in order to use AI tools effectively,” the authors write. “They will also need to know how to critically appraise AI systems to evaluate their potential applications, benefits and limitations in the clinical setting.”
5. AI has the potential to increase the accuracy and efficiency of care, leaving more time for physicians to spend with patients and preserving the empathetic care patients desire. Healthcare consumers understandably worry about AI coming between themselves and their clinicians, replacing the human touch with robotic detachment, the authors note. Many medical students, including those mulling radiology, share the apprehension.
Here Darras et al. bring their discussion back to where it started:
The question raised by the concerned first year medical student about AI replacing radiologists is echoed all around us. It is not just students—but also our colleagues and patients—who worry for the future of radiology. This is an opportunity to arm ourselves with knowledge of AI to dispel any AI misconceptions for patients and learners, foster trust between them and the future state of healthcare and encourage learners to pursue a career in radiology.”
The paper is available in full for free.
Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.