AI Into Action … Finally
After waves of concern and optimism about the impact of machine learning, the real work begins.
Some providers have begun to embrace technologies that, until recently, they considered hype.
Radiologists have gone through a huge swing of emotions when it comes to artificial intelligence.
Two years ago at the annual meeting of the Radiological Society of North America, the pervasive feeling was apprehension. Before the conference, some articles surfaced suggesting that the use of computer technology would eliminate the need for radiologists, because computers could handle all interpretation of images.
I’m not sure where this paranoia landed on the Gartner Hype Cycle, but there was palpable pushback against the threat of AI.
Fast forward to the next year, when some of those fears subsided. More vendors were touting the potential of AI and how it would fit into future applications.
Now, some leading healthcare organizations are beginning to employ AI and machine learning to automate processes that help detect abnormal structures in images. While the eventual goal is to assist radiologists in more effectively detecting and tracking the progression of diseases, IT executives are beginning to grapple with some of the inherent challenges, writes Linda Wilson in this issue’s cover story.
Her reporting finds that there now are numerous algorithms in various stages of development and in the FDA approval process, and experts believe there could eventually be hundreds or even thousands of AI-based apps to improve the quality and efficiency of radiology.
Now, the trick becomes incorporating AI into the workflows of radiologists so they fit seamlessly into their workday. That’s the focus of providers currently, Wilson writes—moving advanced technologies from experimentation into actual production.