Are AI-powered skin-check tools on the horizon for dermatologists, PCPs?

Reality check?

The state of current efforts to develop consumer apps for checking for skin cancer seems to be summarized well on the website for the MoleMapper. The app was developed by researchers at OHSU to help people track how their moles change over time.

“Mole Mapper is NOT designed to provide medical advice, professional diagnosis, opinion, or treatment. Currently, there is not enough data to develop an app that can diagnose melanoma, but if enough data is collected through Mole Mapper and shared with researchers, it may be possible in the future,” the app’s website says.

OHSU released MoleMapper as an iPhone app in 2015. The aim of this project was to help people track the moles on their skin while also fostering an experiment in “citizen science,” OHSU’s Dr. Leachman told this news organization.

OHSU researchers hoped that the digital images taken by members of the public on cell phones could one day be used to develop diagnostic algorithms for melanoma.

But around 2017, the MoleMapper team realized that they would not be able to create a diagnostic app at this time, Dr. Leachman explained. They could not collect enough data of adequate quality.

And by 2021, it was clear that they could not even develop a successful app to triage patients to assess who needs to be seen quickly. The amount of data required was, at this point, beyond what the team could collect, Dr. Leachman said in an interview.

That was a disappointment because the team had successfully completed the difficult task of creating a confidential pathway for collecting these images via both iPhones and smartphones run on Android.

“We thought if we built it, people would come, but that’s not what happened,” Dr. Leachman said. Many patients didn’t want their images used for research or would fail to follow up with details of biopsy reports. Sometimes images were not captured well enough to be of use.

“You need at least hundreds of thousands, if not millions, of data points that have been verified with pathologies, and nobody was giving us back that data. That was the reality,” Dr. Leachman said.

There were valuable lessons in that setback. The OHSU team now has a better grasp of the challenges of trying to build a data-collection system that could prove helpful in assessing skin lesions.

“If you don’t build it, you don’t know” what can go wrong, she said.

Dr. Leachman said other scientists who have worked on similar projects to build skin-analyzing apps have probably encountered the same difficulties, although they may not reveal these issues. “I think that a lot of people build these things and then they try to make it into something that it’s not,” she said.

In addition to the challenges with gathering images, dermatologists frequently need to rely on touch and other clues from in-person visits when diagnosing a suspicious lesion. “There’s something about seeing and feeling the skin in person that can’t be captured completely with an image,” Dr. Leachman said.
 

Public demand

Still, regulators must face the strong and immediate interest consumers have in using AI to check on moles and skin conditions, despite continuing questions about how well this approach might work.

In June, Google announced in a blog post that its Google Lens tool can help people research skin conditions.

“Just take a picture or upload a photo through Lens, and you’ll find visual matches to inform your search,” Google said in a blog post. “This feature also works if you’re not sure how to describe something else on your body, like a bump on your lip, a line on your nails or hair loss on your head. This feature is currently available in the U.S.”

Google also continues work on DermAssist, an app that’s intended to help people get personalized information about skin concerns using three photos. It is not currently publicly available, a Google spokesperson told this news organization.

Several skin-analyzing apps are already available in the Apple and Google Play stores. The British Association of Dermatologists last year issued a press release warning consumers that these apps may not be safe or effective and thus may put patients at risk for misdiagnosis.

“Unfortunately, AI-based apps which do not appear to meet regulatory requirements crop up more often than we would like,” the association said. “Additionally, the evidence to support the use of AI to diagnose skin conditions is weak which means that when it is used, it may not be safe or effective and it is possible that AI is putting patients at risk of misdiagnosis.”

Delicate and difficult balancing act

At this time, regulators, entrepreneurs, and the medical community face a delicate balancing act in considering how best to deploy AI in skin care, Dr. Ko said in an interview. (In addition to being one of the authors on the widely cited 2017 Nature paper mentioned above, Dr. Ko served until March as the initial chair of the American Academy of Dermatology’s Augmented Intelligence Committee.)

There are many solid reasons why there hasn’t been speedy progress to deploy AI in dermatology, as many envisioned a few years ago, Dr. Ko said.

Some of those reasons are specific to dermatology; this field doesn’t have a ready set of robust data from which to build AI-driven tools. In this aspect, dermatology is decades behind specialties like radiology, pathology, and ophthalmology, where clinicians have long been accumulating and storing images and other data in more standardized ways, Dr. Ko said.

“If you went to most dermatology practices and said, ‘Hey, let me learn from the data accumulated over the course of your 30-year practice to help us develop new tools,’” there may not be a whole lot there,” Dr. Ko said.

Beyond the start-up hurdles is the larger concern Dr. Ko shares with other dermatologists who work in this field, such as Dr. Daneshjou and Dr. Leachman. What would clinicians without much dermatology training and patients do with the readings from AI-driven tools and apps?

There would need to be significant research to show that such products actually help get people treated for skin diseases, including skin cancer.

Dr. Ko praised Google for being open about the stumbles with its efforts to use its AI tool for identifying diabetic retinopathy in a test in Thailand. Real-world hitches included poor Internet connections and poor image quality.

Developing reliable systems, processes, and workflows will be paramount for eventual widespread use of AI-driven tools, Dr. Ko said.

“It’s all those hidden things that are not sexy,” as are announcements about algorithms working about as well as clinicians in diagnosis, Dr. Ko said. “They don’t get the media attention, but they’re going to be make or break for AI, not just in our field but [for] AI in general.”

But he added that there also needs to be a recognition that AI-driven tools and products, even if somewhat imperfect, can help people get access to care.

In many cases, shortages of specialists prevent people from getting screened for treatable conditions such as skin cancer and retinopathy. The challenge is setting an appropriate standard to make sure that AI-driven products would help most patients in practice, without raising it so high that no such products emerge.

“There’s a risk of holding too high of a bar,” Dr. Ko said. “There is harm in not moving forward as well.”

A version of this article first appeared on Medscape.com.