at a time of limited access to burned-out doctors, mass exodus of nurses, increasingly long patient waitlists, and an ongoing pandemic, the use of artificial intelligence in the medical system has massive potential. being able to diagnose — or at least flag — significant issues before setting foot in a doctor’s office would help thousands of people. and the possibility of ai diagnosing something with visible physical symptoms would be a natural place to start.
but unfortunately, with skin cancer, the existing ai just isn’t good enough.
that’s what researchers from the u.k.’s national cancer research institute (ncri) discovered when they examined the way ai learns about skin cancer, in a study published this week
in the lancet
.
“ai programs hold a lot of potential for diagnosing skin cancer because it can look at pictures and quickly and cost-effectively evaluate any worrying spots on the skin.” dr. david wen of university of oxford
told the ncri’s news outlet
. “however, it’s important to know about the images and patients used to develop programs, as these influence which groups of people the programs will be most effective for in real-life settings.”
ai learns what it’s looking for through “training”: being fed thousands of images of skin lesions and other abnormalities that have already been determined as either cancerous or non-cancerous. in theory, the program can then track and flag the similarities that may lead to a cancer diagnoses in new photos.