Researchers say they’ve been able to measure recovery from treatment-resistant depression through brain scans — a crucial step toward quantifying the impact of therapies on a condition whose progress is notoriously difficult to measure objectively. And that’s thanks to generative AI, they say.
In a small study published Wednesday — just 10 people with severe, treatment-resistant depression receiving deep brain stimulation therapy — researchers used the electrodes to record brain activity and later fed the scans into a homegrown artificial intelligence system that analyzed them for patterns. They found that it was possible to track patients’ recovery through changes in brain cells’ electrical activity.
advertisement
Finding so-called biomarkers, or objective measurements reflecting depression, could help diagnose depression, track its progression, predict a relapse, and better tailor therapies to individual patients. But finding those metrics has been difficult, partly because depression’s biological impact isn’t well understood.
Get unlimited access to award-winning journalism and exclusive events.
Subscribe Log In
Previous article：
Venture capitalist Bob Kocher on the state of digital health
Next article： New Eli Lilly Alzheimer’s data poses Medicare coverage conundrum
Next article： New Eli Lilly Alzheimer’s data poses Medicare coverage conundrum
