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AI / informaticsJournal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG · 2026

AI-assisted diagnosis of nail unit melanoma and melanonychia using a clinical deep learning model.

Yusung Chu, Sejung Yang, Jin-Woong Jung … Byungho Oh

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DermatologyAI / informatics

Deep learning model separated nail unit melanoma from benign melanonychia on clinical photographs

AI-assisted diagnosis of nail unit melanoma and melanonychia using a clinical deep learning model.

Yusung Chu … Byungho Oh

Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG · 2026

Background

Nail unit melanoma (nail unit melanoma) is a rare but potentially fatal malignancy often misdiagnosed as melanonychia.

Purpose

This study aimed to develop and validate an artificial intelligence model to distinguish nail unit melanoma from benign melanonychia using clinical images and to assess its diagnostic utility through human comparison and external validation.

Methods

Clinical images from 172 patients with melanonychia and 122 patients with nail unit melanoma were retrospectively collected.

n = 172 patients

Results

how well the AI told nail melanoma (a nail cancer) from harmless nail pigment - higher is better

More results

ResNet-50 achieved the highest sensitivity (87.2 %).

Convolutional neural networks assistance improved the diagnostic accuracy of all human raters (accuracy increased from 70.0 % to 80.8 %), with dermatology residents showing the largest gain.

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Conclusion · 1 of 2

The proposed convolutional neural networks-based models demonstrated robust performance in differentiating nail unit melanoma from melanonychia and improved diagnostic accuracy and agreement among human evaluators.

Conclusion · 2 of 2

While not intended to replace clinical judgment, this approach shows promise as a supportive screening tool in clinical settings, warranting further validation in larger, multi-institutional, and multi-ethnic cohorts.

Post

AI-assisted diagnosis of nail unit melanoma and melanonychia using a clinical deep learning model.

Deep learning model separated nail unit melanoma from benign melanonychia on clinical photographs

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