In just five years, from 2015-2020, the percentage of radiologists using some form of AI has gone from zero to 30.
That’s according to a 2020 study from the American College of Radiology on radiologist uptake of AI, and in a recent interview with HealthcareITNews, Dr. Keith Dreyer, chief data science officer and vice chairman of radiology at the Mass General Brigham health system, gives an overview of how his organization has moved quickly to incorporate AI into many aspects of their operation, including radiology.
In 2016, for example, “we launched the Center for Clinical Data Science (CCDS), a full-sized team solely focused on creating, promoting and translating AI into tools that will enhance clinical outcomes, improve efficiency and enhance patient-focused care. We also created what was, at the time, the largest GPU supercomputer ever deployed at an academic medical center to help process the vast amount of data we were beginning to collect.”
Fast forward to the onset of the COVID-19 pandemic, and Dreyer points out that’s pretty much time time they started to deploy AI in their clinical practices, and “this is where our early efforts began to deliver value. Though we had started our AI research years earlier, the pandemic created a surge in use-case opportunities with the adoption of virtual visits, remote technology and a continuum of information flow that allowed us to use AI more naturally.”
Because of those investments, they now have their own data sets and have developed more than 50 algorithms for use in their clinical practice, some of which have been FDA-cleared for commercial distribution.
In Dreyer’s view, “AI will become more mainstream in clinical care over the next few years, and it will become an essential part of the diagnostic care process. We also foresee AI predictions utilizing multimodal data sources to drive decisions for triage and disease management through the integration of AI within the electronic medical record.”
For radiologists in particular, Dreyer sees AI becoming a critical tool.
“We've come a long way from five years ago when some predicted AI would replace radiologists,” he said. “Instead, we see AI as augmenting the radiologist's intelligence – automating redundancies and optimizing the way radiologists practice. Not just saving time, but enhancing the diagnosis and potentially preventing what could have been an easy miss will also be critical.”
In short, he says, “with intelligent workflow, radiologists can practice at the top of their license with maximum efficiency, accelerating their ability to deliver optimal value and enable the best patient care possible.”