paper
arXiv cs.CV
November 18th, 2025 at 5:00 AM

DermAI: Clinical dermatology acquisition through quality-driven image collection for AI classification in mobile

arXiv:2511.10367v2 Announce Type: replace Abstract: AI-based dermatology adoption remains limited by biased datasets, variable image quality, and limited validation. We introduce DermAI, a lightweight, smartphone-based application that enables real-time capture, annotation, and classification of skin lesions during routine consultations. Unlike prior dermoscopy-focused tools, DermAI performs on-device quality checks, and local model adaptation. The DermAI clinical dataset, encompasses a wide range of skin tones, ethinicity and source devices. In preliminary experiments, models trained on public datasets failed to generalize to our samples, while fine-tuning with local data improved performance. These results highlight the importance of standardized, diverse data collection aligned with healthcare needs and oriented to machine learning development.

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Canonical link: https://arxiv.org/abs/2511.10367