The University of Alicante (UA) and the Sant Joan d'Alacant University Hospital have collaborated to launch MEL-IA (MobilE skin Lesion dIAgnosis), an artificial intelligence system designed to automate the classification of skin lesions.
The system incorporates a mobile app to capture images of skin lesions—such as moles or spots—and record clinical data, an AI model to perform the classification, and complex integration models that securely connect all data with hospital systems.
Unlike tools designed solely to distinguish between malignant and benign lesions, MEL-IA provides differential categorization across five major skin lesion types: melanoma, naevus, basal cell carcinoma, actinic keratosis, and benign keratosis.
Results indicate that the system achieves an overall accuracy of 86%. The UA researchers noted that for melanoma detection, MEL-IA achieved a sensitivity of 88%, while reaching 92% for basal cell carcinoma, adding that the highest overall scores corresponded to naevi and basal cell carcinomas.
A key highlight of the project is that the technology moved beyond the experimental stage to deployment at the Sant Joan d'Alacant University Hospital to evaluate performance in a live healthcare environment.
The team highlighted that they processed 980 dermatological studies with response times under one second.
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