AI applications are entering clinics at a rapid rate, and physicians have met the technology with equal parts excitement about its potential to reduce their workload and fear about losing their jobs to machines.^[i]

 

Who’s afraid of the big bad computer? Apparently, some radiologists—and even medical students contemplating entering that field—are fearful of being replaced by computers.

Not all radiologists, or physicians in general, have anxiety over the entrance of Artificial Intelligence (AI) onto the stage of medicine. On the bright side, AI is already reading imaging scans such as MRI, and improving the efficiency and accuracy of diagnosis. AI has the potential to liberate doctors for greater contact time with patients, to improve clinical care in locations where doctors and imaging centers are in short supply, and to help researchers explore the mysteries of diseases for which there is no cure.

On the darker side, a sort of medical propaganda has planted a myth into the minds of doctors and patients alike. The myth is that the field of diagnostic imaging will inevitably succumb to obsolescence as Deep Learning trains itself to diagnose disease and dominate the field. At its logical extreme, this notion has overtones of science fiction scenarios in which computers enslave their human masters.

Radiology: subjective skill or objective science?

The ever-increasing and unstoppable momentum of AI in medicine is reflected by the numbers:

Publications on AI have drastically increased from about 100–150 per year in 2007–2008 to 700–800 per year in 2016–2017. Magnetic resonance imaging and computed tomography collectively account for more than 50% of current articles. Neuroradiology appears in about one-third of the papers, followed by musculoskeletal, cardiovascular, breast, urogenital, lung/thorax, and abdomen, each representing 6–9% of articles. With an irreversible increase in the amount of data and the possibility to use AI to identify findings either detectable or not by the human eye, radiology is now moving from a subjective perceptual skill to a more objective science.^[ii]

The distinction between “perceptual skill” and “objective science” sounds like the two are polarized. In reality, radiologists integrate both perception and science. I would also add experience, which is a natural exponential accrual of learning somewhat analogous to the Deep Learning aspect of AI. While life experiences evolve more slowly than supercomputers processing millions of image elements and calculating probabilities, each radiologist’s brain is developing exponentially just as Deep Learning does.

Radiologists are educated and trained in their skills, and keep abreast of current scientific developments in the field. However, they also possess irreplaceable human qualities that are the heart and soul of the healing arts: empathy, passion for their work, and desire to make life better for their patients.

Commentator Erik L. Ridley suggests that radiologists take the tiller and navigate away from gathering clouds of negative propaganda. He urges radiologists to use social media to head in the direction of a safe harbor of optimism and opportunity. Social media is a powerful tool for shifting perceptions and beliefs, and Ridley identifies five areas in which radiologists can exercise positive influence:

1. Use an active online presence to connect with peers in your own and other specialties, patients, advocacy groups and healthcare entities. Consider online/Twitter events to educate the lay public and “remind their colleagues and patients that they remain advocates for best practices in multiple settings, according to the authors.”
2. Connect with the media to promote the positive future for radiology.
3. Discuss patients’ imaging results with them, and if AI was used, explain how it helped in the diagnosis, and that it doesn’t function alone but helps the radiologist.
4. Work as partners with technology developers, not as competitors.
5. Make explicit the role played by radiologists in developing AI, ensuring its ethical and safe use.^[iii]

It’s no coincidence

My desire some weeks ago to begin a series of blogs on Artificial Intelligence originated from my own fascination with it. It’s an exciting development and, if used wisely and well, can culminate in improved healthcare and quality of life for everyone. Thus, I don’t share what I see as misplaced worry that AI will somehow dominate the field of radiology.

That said, when I came across Ridley’s article, I felt it was no coincidence that I had already determined to present the pros, cons, and my own conclusions about the role of AI in radiology and medicine in general. AI is an idea whose time has come, and it can only become more prevalent. I hope that by doing this series, I can play a part in portraying the positive contribution I believe AI will ultimately offer doctors and patients everywhere.

NOTE: This content is solely for purposes of information and does not substitute for diagnostic or medical advice. Talk to your doctor if you are experiencing pelvic pain, or have any other health concerns or questions of a personal medical nature.

References

[i] Reardon, Sara. “Rise of Robot Radiologists.” Nature, Dec. 18, 2019. https://www.nature.com/articles/d41586-019-03847-z
[ii] Pesapane, F., Codari, M. & Sardanelli, F. Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp 2, 35 (2018).
[iii] Ridley, Erik. 5 ways rads can use social media to shift AI narrative. Aunt Minnie, June 19, 2020. https://www.auntminnie.com/index.aspx?sec=sup&sub=aic&pag=dis&ItemID=129337