“Hopefully, in the not-too-distant future, doctors and nurses may start getting a warning a day or two before for these acute causes of patient deterioration,” Dr. Dominic King, DeepMind’s health lead and coauthor of the research paper, told CNN Business.
The work is still in the early stages, and there are some caveats that accompany the results: The researchers noted their system gave two false alerts for every true alert of a kidney injury. And nearly all the patients in the dataset the researchers used (about 94%) were male, so it’s not yet known if the work would be similarly helpful for spotting kidney failure in women.
But it advances what’s known about how deep learning — a form of AI modeled after the way neurons work in the brain, which ingests loads of data and learns to make its own predictions — may be helpful in healthcare.
Kidney issues in particular are tricky to identify in advance. These days, doctors and nurses are alerted to acute kidney injury via a patient’s blood test, King said, but by the time that information comes through, the organ may already be damaged.
The research isn’t yet ready for clinical practice but it’s impressive, said Eric Topol, a professor at Scripps Research and author of “Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again.” He believes it could eventually be helpful in part because doctors are simply bad at making predictions about what will happen to individual patients.
“We think someone’s going to die and then they’re like Lazarus, or we think they’re going to not be readmitted and they come back in an hour. We’re just not good at this,” he said. “Applying deep learning for this common and serious issue, kidney injury — that’s really smart.”
Before rolling an AI system out with any patients, though, King said the researchers would need to make sure their model works accurately with patients of different genders and backgrounds.
READ MORE HERE