A research team is developing an artificial intelligence-powered at-home test for diagnosing skin reactions. The new system aims to offer a remote solution for conditions such as allergic contact dermatitis, which affects approximately one in five people.
The AI test seeks to streamline the diagnostic process for stubborn rashes, which traditionally require multiple, sometimes costly, visits to a dermatologist. The research team, led by Dr. Allison Bruce, explored whether artificial intelligence could interpret photographs of skin reactions, addressing challenges patients face in accessing specialized care.
To train the artificial intelligence, researchers provided it with data, specifically 28,000 patch test images collected over the last decade through their system. They then compared the AI’s interpretations to those of dermatologists.
The team found the AI performed effectively.
“We found that the AI was pretty much as good as the dermatologist in interpreting the photographic images,” Dr. Bruce said.
During the testing phase, patients still visited the clinic, but the ultimate goal is for people to conduct much of this process from home, capturing photos with their phones for AI interpretation.
Natalie Thackerdin, a pharmacist and trial participant, found the concept innovative.
“Having AI as a potential to read these results, I think that’s really cool and innovative,” Thackerdin said.
The remote testing system offers convenience for participants. Guillermo Pradieu, a GI researcher and trial participant, noted the ease of the process.
“So it was pretty convenient, pretty straightforward. It didn’t take more than a few minutes for him to basically read it using the AI algorithm,” Pradieu said.
Dr. Bruce emphasized the difficulties patients often encounter in obtaining specialized care.
“It’s also sometimes very hard for patients to get access to a dermatologist,” Bruce explained.
The researchers hope the AI system can alleviate this burden.
“We hope to reduce the burden on patients so that they don’t have to come in, but instead be able to potentially do that remotely through photography and AI helping to interpret,” Bruce stated.
Researchers are now training the AI to handle real-world variables, including different phone models, lighting conditions and camera angles.
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