Autonomous artificial intelligence (AI) as a medical device could be used to address rising dermatology service needs, freeing up clinical capacity to provide about 8,500 more dermatology appointments within 16 months, according to findings from a real-world U.K. study presented at the European Academy of Dermatology and Venereology (EADV) Congress 2026 (Abstract P2827).
“We believe the greatest value of autonomous AI lies not in the technology itself, but in the specialist capacity it unlocks. Every hour saved reviewing low-risk lesions can be reinvested in patients with skin cancer, helping them access timely treatment to improve prognosis, and in patients with severe inflammatory skin disease, where earlier access to specialist care and effective treatments can transform quality of life,” said lead study author Lucy Thomas, MPharm, MBChB, MRCP UK, a National Health Service (NHS) Consultant Dermatologist at Chelsea & Westminster Hospital and an honorary clinical lecturer at Imperial College London.
Background and Study Methods
In the U.K., urgent suspected skin cancer referrals have more than doubled since 2009, even though only about 6% result in a true urgent skin cancer diagnosis. Dermatologist roles also remain an unmet need, with about one in four roles in the U.K. unfilled, limiting their capacity and further challenging dermatology services.
Researchers believe that autonomous AI as a medical device could provide a scalable solution, but real-world evaluation is needed. The study sought to evaluate the real-world safety, diagnostic performance, and service impact of using autonomous AI to triage patients within urgent suspected skin cancer pathways.
After a validation period, researchers implemented a CE-marked Class III autonomous AI as a medical device system across two NHS hospital sites. The system implementation was evaluated for 16 months.
Skin lesions were classified through clinical and dermoscopic smartphone images. Benign cases were autonomously discharged and higher-risk cases were referred for teledermatologist review.
To evaluate the impact of the system, performance was compared across face-to-face, teledermatology alone, and AI-assisted teledermatology pathways at the same hospital.
Key Findings
Ninety-four percent of urgent suspected cancer referrals were managed through the AI-assisted teledermatology pathway, while 6% of cases that were not appropriate for teledermatology were handled with face-to-face management.
The AI system discharged 31% of patients at the first hospital site and 25% at the second without clinician review. Teledermatologists discharged another 24% from the first site and 25% from the second.
Autonomous AI reduced the number of patients requiring follow-up care from 27% to 12%. Biopsy rates were also lower with autonomous AI vs standard face-to-face management (43% vs 27%).
The AI-assisted pathway saved approximately 2,851 clinician hours, which amounted to about 8,553 additional face-to-face dermatology appointments that could have been made or were made during the study period.
The researchers noted that six false-negative cases were discharged through the AI-assisted pathway, which were later identified in postmarket surveillance.
“One of the key lessons for us is that deploying an AI system safely isn't a one-off exercise,” said Dr. Thomas. “You need to keep monitoring it, understand when things go wrong, learn from those cases and make sure patients themselves know what to look out for.”
“If these findings are replicated across larger populations and different health-care settings, autonomous AI could become an important part of creating a more sustainable dermatology service—not by replacing dermatologists, but by allowing scarce specialist expertise to be focused where it can make the greatest difference to patients’ lives,” Dr. Thomas concluded.
DISCLOSURES: The study was partly supported by a grant from La Roche-Posay (L’Oreal Dermatological Beauty), and the AI medical device was funded by Chelsea & Westminster Hospital NHS Foundation Trust. For full disclosures of the study authors, visit eadv.org.
