As a radiologist, the worry regarding whether AI will take over the role of radiologists is a query I’ve faced often, particularly from medical students at a pivotal point in their career choices. During my own education, I experienced similar fears. Nevertheless, my journey in medicine and my observations of AI’s advancement lead me to a definitive conclusion: AI is not replacing radiologists. Those proposing otherwise may not fully grasp our professional responsibilities or might have hidden agendas.
Radiologists do not simply analyze images; we are integral clinical players. Our responsibilities include examining patient histories, evaluating lab results, linking clinical stories, employing various software to integrate external imaging, and consolidating all this information into actionable reports. This procedure also requires communication with referring physicians and guiding further actions, demanding a level of human judgment that AI lacks.
AI companies frequently exaggerate the prospect of total automation in radiology. A key element they frequently miss is the distinct character of hospitals. Each facility possesses unique electronic medical records (EMRs), imaging systems, and workflows. Aligning these systems to support automation entails an expensive overhaul that overwhelmed hospitals cannot manage.
Even with potential technological progress in certain radiologic functions, execution would require a significant infrastructure revamp, strong IT support, and broad acceptance, all of which remain far-off realities. While AI has generated considerable enthusiasm, its actual impact on health care is still limited.
Worryingly, the fears regarding AI are discouraging skilled students from entering the field of radiology, which harms not only the discipline but also patient care. Radiology presents intellectual challenges, is essential to clinical functions, and continues to be crucial in contemporary medicine. AI, when fully developed, might augment our skills but cannot replicate the vital human components required today.
In my engagement with research in radiology AI, I have noticed that findings from these studies often align with particular narratives. AI’s output is sometimes unjustly compared to radiologists performing the same tasks casually, highlighting a distinction from the intensity required in clinical practice and emphasizing AI’s present limitations.
The motivation behind some AI companies seems to lean toward replacement rather than synergy. This perspective downplays the complexities of health care. The essence of health care lies in human relationships, grounded in trust, empathy, communication, and judgment—all elements that AI inherently cannot mimic. Reducing patient care to mere algorithms overlooks the invaluable human spirit that is essential to its foundation.
Fardad Behzadi, Radiologist.