AI In Radiology Today
What role does AI have in radiology? How is AI affecting physicians? This blog post will help to answer these questions by exploring how AI is being implemented in radiology departments today and what effect it has on the role of a radiologist.
One of the first companies to implement AI algorithms into a radiology practice and achieve substantial results was Global Diagnostics Australia, a diagnostic imaging company. They utilized an AI system that was designed to reshape the workflow of the practice by prioritizing patients in a critical state. The system would sort through medical images and alert radiologists if there was an urgent case that needed attending. The algorithms also allowed the process of diagnosing images of the head, neck, or chest to be quicker.
At the University of Rochester, Resident Doctor Komal Chugtai described AI as an incredible help when dealing with large workloads. She also said that when the AI tagged a case as urgent it sometimes delivered her to a critical problem sooner.
In San Diego, Dr. Eric Grey, a resident doctor at UC San Diego says that he uses AI to quickly assess all his cases at the beginning of the day giving him a basic analysis of the images. This often helps with the diagnosis of simple images, which would otherwise be a tedious task for a radiologist. He also twice a day has the AI run through images to alert him of any urgent cases.
These examples illustrate that the relationship between AI and radiologists is mainly harmonious; AI can serve to smooth the workflow of a radiology department and help lift some of the weight off the shoulders of physicians.
This impact of AI can help to lessen the extent of physician burnout among radiologists. Physician burnout is a large problem in the medical field and radiology is heavily affected by it. The findings of the Medscape Radiology Lifestyle, Happiness and Burnout Report 2019 show that 44% of radiologists reported that they experience burnout in some capacity. Some of the central reasons reported for this burnout were endless tasks and long hours. To cope with burnout self-care techniques such as mediation are recommended, but AI has also been found to help address the issue. AI can serve to be an extra measure to make sure mistakes are not made, and though it cannot be relied on entirely in all situations, it can give radiologists a greater sense of security in their diagnosis. Additionally, AI, as mentioned above, takes on some of the mindless tasks that a radiologist would have to handle, helping to relieve some stress from the doctor. These benefits of AI can help solve the issue of burnout, keeping radiologists happier and working for longer
The role that AI has with physicians is sure to shift as the technology improves and what the role of a radiologist might be in the future is certain to be different from their role is today; however, hopefully by exploring how AI is used in radiology, you have gained a greater understanding of AI’s common uses in the field and its effects on physicians.
References:
https://www.aidoc.com/blog/artificial-intelligence-in-radiology/ https://appliedradiology.com/articles/the-radiologist-s-gerbil-wheelinterpreting-images-every-3-4-seconds-eight-hours-a-day-at-mayo-clinic https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6268174/ diagnosticimaging.com/view/ai-and-future-radiology
Zach Gorton is a Student Ambassador in the Inspirit AI Student Ambassadors Program. Inspirit AI is a pre-collegiate enrichment program that exposes curious high school students globally to AI through live online classes. Learn more at https://www.inspiritai.com/.
