AI Triage Could Free Up Dermatology Capacity
UK study reports 2,851 clinician hours saved, but safety monitoring remains essential
Key Developments:
- AI triage saved an estimated 2,851 clinician hours
- Monitoring identified six skin cancer cases initially missed by AI
(Medical Xpress) — October 12, 2026: An artificial intelligence system used to assess urgent suspected skin cancer referrals could help expand dermatology services by reducing the number of low-risk cases requiring direct specialist review, according to research presented at the 2026 European Academy of Dermatology and Venereology (EADV) Congress in Vienna.
The study, led by Lucy Thomas of Imperial College London and colleagues working across two UK hospital sites, evaluated an autonomous AI medical device over a 16-month period. The system analysed clinical photographs and dermoscopic images, assessing skin lesions and directing higher-risk cases for review by a teledermatologist.
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Patients whose lesions were classified as benign could be discharged without an individual clinician reviewing their cases. The system used image-quality checks and a structured classification process to support its decisions, with the aim of reserving specialist attention for patients requiring further investigation.
Researchers evaluated 8,391 patients through the autonomous pathway. Overall, 86 per cent consented to autonomous decision-making, indicating substantial acceptance among the patients included in the study.
Following exclusions, the AI system independently discharged 31 per cent of patients at one hospital and 25 per cent at the other. Teledermatologists subsequently discharged an additional 24 per cent and 25 per cent, respectively.
The researchers estimated that the approach saved 2,851 hours of clinician time compared with conventional face-to-face assessment, representing a 62 per cent gain in clinical capacity. Based on 20-minute appointments, the recovered time could accommodate more than 8,500 additional face-to-face dermatology consultations.
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Thomas said: "We believe the greatest value of autonomous AI lies not in the technology itself, but in the specialist capacity it unlocks."
The emergency patient journey and where artificial intelligence is making or can make an impact. AI: artificial intelligence; ED: emergency department; EMD: emergency medical dispatch.1. CREDIT: News Medical LifeSciences.
The results also showed changes in follow-up and biopsy patterns. Routine follow-up fell from 27 per cent under standard teledermatology to 12 per cent with the autonomous pathway. Biopsy rates were also lower than those recorded under conventional face-to-face care, although differences between care pathways should be interpreted in the context of patient selection and clinical practice.
However, the findings do not establish that autonomous AI can identify every skin cancer correctly. Additional safety reporting identified six false-negative cases that had initially been discharged through the pathway. These included five basal cell carcinomas and one melanoma in situ, subsequently identified through post-market surveillance.
The wider safety assessment reported sensitivity above 98 per cent for invasive melanoma, squamous cell carcinoma and basal cell carcinoma, with an overall specificity of 72.1 per cent. These measures describe performance across the assessed dataset and should not be interpreted as a guarantee that an individual patient will receive a correct classification.
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Thomas has also emphasised the importance of ongoing safety oversight. In related research coverage, she said: "One of the key lessons for us is that deploying an AI system safely isn't a one-off exercise."
Continued monitoring can help healthcare teams identify missed diagnoses, investigate failures and refine clinical pathways. Patients also need clear instructions about what to do if a skin lesion changes or new symptoms develop after an automated assessment.
The findings arrive amid pressure on dermatology services, where growing referral volumes and workforce shortages can delay access to specialist care. If further evaluations support the results, autonomous triage could help hospitals direct clinical resources towards suspected cancers and other complex skin conditions requiring timely intervention.
Autonomous artificial intelligence (AI) in urgent skin cancer pathways can increase clinical capacity for dermatologists, according to a study presented at the annual meeting of the European Academy of Dermatology and Venereology, held from Sept. 30 to Oct. 3 in Vienna.
Nevertheless, the study involved two UK hospital sites, and its results may not translate directly to every healthcare system. Differences in patient populations, image quality, clinical protocols and access to follow-up care could affect performance elsewhere. The technology should therefore be assessed in the context of local clinical governance, patient consent and reliable safety monitoring.
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The study was partly supported by a grant from La Roche-Posay, part of L'Oréal Dermatological Beauty, while the medical device was funded by Chelsea and Westminster Hospital NHS Foundation Trust. These funding disclosures are relevant when evaluating the evidence and reinforce the importance of independent assessment.
The research suggests that autonomous AI may help increase dermatology capacity, but its value depends on more than the number of appointments made available. Reliable detection, transparent oversight and prompt follow-up remain essential to ensure that efficiency gains do not come at the expense of patient safety.
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