AI and deep learning have a wide range of applications and potential in radiology – spanning from improved diagnosis, enhanced workflow and inevitably, a shift in the radiologist’s role.
The ability to mine the endless amounts of imaging data is driving AI innovation forward in radiology; however, as this disruptive technology and its data applications begin to find a more defined role, there are questions around its impact on the future of the industry.
One question top of mind for many in the field is: Will AI replace radiologists? A recent article in JAMA analyzes this question and the answer extends past a redefined role and into a new field altogether, suggesting that as information specialists, radiologists won’t lose their jobs.
Rather, their roles will be redefined and may ultimately merge with the other key information specialists in healthcare – pathologists—thus creating well rounded information specialists who may have a deeper and broader look into diagnoses and treatment pathways.
While automation enhances and improves the role of information specialists, there is still a need for the human perspective.
AI in radiology, for example, is designed to help tease out and prepare data for the radiologist, but as it relates to evaluating scans and diagnosis, the understanding of the interaction between the imaging physics and the disease biology is better done by the radiologist.
A merging of these two data-rich fields would allow the information specialist to interpret the important data and manage the information in the clinical context of the patient to help guide clinicians. It’s a natural combination in this perspective and there are three phenomena happening now driving this compelling integration:
And while the future will likely hold a different role for the radiologist, the importance and clinical need for radiology will only increase.
