10/24/2019
If you think AI will never replace radiologists — you may want to think again
If you think AI will never replace radiologists — you may want to think again Usm systems Oct 24 · 2 min read
This is one of the most discussed questions in radiology today: What impact does artificial intelligence (AI) have on radiologists? Radiologist Robert Skier of Rod Net shared his own thoughts on the subject in a new commentary published in the Journal of the American College of Radiology — and he is not as optimistic as some of his peers across the industry.
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The advent of computers that can accurately interpret diagnostic imaging studies will upend the practice of radiology,” Schier wrote. “The two currently unanswered questions are just how much upending there will be and how long it will take to happen. https://medium.com/@fugenxmobileapp/if-you-think-ai-will-never-replace-radiologists-you-may-want-to-think-again-937649a803b0
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10/24/2019
If you think AI will never replace radiologists — you may want to think again
There are vastly differing opinions, from the apocalyptic claim that AI Services will make all radiologists extinct to the delusional assertion that computers will always merely assist — and never replace — radiologists. Both extremes are mistaken, but the truth is in the direction of the first.” Schier noted that some radiologists look to the current limits of AI as proof that technology can never take over the work of radiologists. However, he does not agree with this line of thinking. “This is an understandable reaction from a practicing radiologist, but it is like watching and trusting a kindergartener because she cannot add or remove well, she cannot read an abdominal ultrasound,” he wrote. “It umes limits to non-existent computer intelligence.” In fact, it is easy for people to see AI technology as “a collection of circuits on the console” and begin to see “an army of fellowship-trained radiologists with photographic memories, an IQ of 500 and no excuse”. Food or sleep. “ Motivational programs and improved processing speeds have helped AI programs take the leap when it comes to interpreting medical images successfully. The Shire explained that programs can also rewrite their own programming as needed, which means that they are already attacking problems “in a way that we sometimes don’t understand.” Schier concludes his comment by looking at how the number of horses in the United States has fallen from 25 million to 6 million over the course of four decades of the discovery of machine power. Unless radiologists begin to take on more responsibility outside of interpreting studies, the number of radiologists in the United States may see its own significant decrease. Want to know more about AI services then have a free visit for USM systems
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