As A.I. takes over the grunt work, doctors can get back to healing
A.I. has the power to transform the world — at least that’s what we’re constantly being told. Yes, it powers voice assistants and robotic dogs, but there are some legitimate areas where A.I. is not only making things easier and more convenient. In the case of medicine and health care, it’s actually saving lives.
There has been pushback lately, though. Medical professionals and government officials are bullish about the long-term potential of artificial intelligence’s transformative powers, but researchers are taking a more cautious and measured approach to implementation. In just the past year, we’ve seen huge leaps forward that take A.I.’s potential in medical care and turn it into a reality.
Today, we stand on the brink of a significant transformation in how we’ll all experience and use our medical data in the future.
“We became serious about it as a discipline maybe five years ago, but my whole career I’ve been haunted by the need for this technology,” Dr. Richard White told Digital Trends about the institution’s foray into A.I.. He’s the chair of radiology at Ohio State University’s Wexner Medical Center
“For the longest time, I could not figure out why there wasn’t a use for computers to replicate what humans are doing – to laboriously look through all the images that were dynamic and try to come up with this, and then have the computer make the same mistakes that I was making was very frustrating for at least three decades.”
White said that when they tried to venture into radiomics, they saw a true need for computer smarts. “About four or five years ago, things were coming together and it was the right thing to do. It was meeting a dire need, and that’s when we started serious [with A.I.] in our labs.”
Radiologists from participating health systems at GTC this year, including White, Dr. Paul Chang, a professor and vice chairman from the University of Chicago, and Dr. Christopher Hess, a professor and chair of radiology from the University of California, San Francisco (UCSF), began exploring A.I. simply because the amount of medical data from improved imaging scans became overwhelming.
Advances to medical imaging technology resulted in the collection of significantly more patient data, Chang and his colleagues said, which led to doctor burnout. Doctors see A.I.’s transformative potential, as the technology could allow them to regain some of the time spent on laboriously going through scans, and this, according to Dr. Hess, allows “doctors to become healers again.”
But Chang cautions his fellow practitioners from being “seduced” by the new technology, noting that it must be correctly implemented to be effective. “You can’t prematurely incorporate A.I. into a system that’s broken,” he said.
In many ways, it’s that exact scenario that has led us to where we are today.
The current practice of medicine right now is centered around algorithms and electronic health records. This software isn’t centered on patient care or learning, but it’s a system of categorizing treatments, which in turn allows insurers to pay doctors for services that were performed.
“The industry has transformed doctors into clients to put in codes so that they can be billed,” Dr. Walter Brouwer, CEO of data analytics firm Doc.A.I. said. “We have to stop what we’re doing because it doesn’t work. If you take 2019, the predictions are that 400 doctors will commit suicide, 150,000 people will die, and the first course of bankruptcy will be medical records, so we trust that everyone will try to fix a system that’s unfixable. It’s up to the patient and the doctors to try to fix it, because we are the agents of the last resort.”
For White, changing how data flows through the system is an important first step to being able to truly leverage the power of A.I.. Unlike other fields where A.I.
