Five years ago, the experts predicted that the increase in artificial intelligence might become a source of unforeseen challenges for radiologists. AI is practically taking the medical care field by storm. There remains hardly any domain of this sector untouched by the advent of AI.
The diagnostic services have particularly started integrating AI for faster and more accurate outputs. However, contrary to the expectation, the involvement of radiologists has not gone down with the introduction and widespread use of AI in radiology.
The Expectations
When IBM’s Watson, the computer capable of answering questions defeated the Jeopardy Champions, Brad Rutter and Ken Jennings, the domain of technology predicted otherwise. 5 years later, Virginia Rometty, CEO of IBM, remarked in an IT event that radiologists have lost the ground beneath them. She also confirmed that after another 5 years, the potential of AI will be way higher than the radiologists.
Computer scientists too thought that training the radiologists might not be of any use any further. Instead, the implementation of AI should e the future of radiology. A renowned neural network scientist remarked that radiologists will fall off a metaphorical cliff as soon as AI algorithms would take up the task of interpreting data and images.
The Reality
No matter the predictions, radiology has withstood the test of time. It has not succumbed to the might of AI and has managed to keep the rug under human feet. Aish Thamba (BS) and Richard B Gunderman (MD, Ph.D.) of School of Medicine, Indiana University’s radiology department celebrated the anniversary of radiology years after the speculative proclamations.
Their editorial column in Academic Radiology to discuss how much AI has advanced and how far the technology still has to go is the one that reclaimed the importance of radiologists.
The authors clearly stated that Hinton and IBM overestimated the pace of advancement of AI algorithms. Therefore, the new technology has yet not rendered the efficiency and contribution of physicians and radiologists completely unnecessary.
Emphasizing the importance of radiologists in-patient care, the duo further mentioned that Hinton must have misunderstood the extent of the significance of radiologists in medical care. The scope of radiology does not include image interpretation alone. It also involves several other aspects which make the domain human intervention dependent. To substantiate their words, the authors also gave the instance of the Anderson Cancer Center and Watson association. This partnership failed due to many reasons.
A physician’s performance proved way more efficient than Watson’s, for individual patients. A radiologist is not an image interpreter. This role also includes crucial tasks like caregiving, teaching, mentoring, and understanding patients as humans above all.
The scientists missed to consider the human touch lateral into the process and thereby predicted inappropriately. According to the authors, machines can be an excellent help but not a perfect human touch substitution.
In the end, the authors emphasized the need to generate processes and services that fit the requirements of the patients. Fitting the patients into the process can never be the solution. The process should evolve to match the needs of the patients, doctors, and ailments.
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