Advancement and independent validation of a deep learning-based tool for automated scoring of nail psoriasis severity using the modified nail psoriasis severity index

ObjectiveTo improve and validate a convolutional neural network (CNN)-based model for the automated scoring of nail psoriasis severity using the modified Nail Psoriasis Severity Index (mNAPSI) with adequate accuracy across all severity classes and without dependency on standardized conditions.Method...

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Bibliographic Details
Main Authors:	Stephan Kemenes, Liu Chang, Maja Schlereth, Rita Noversa de Sousa, Ioanna Minopoulou, Pauline Fenzl, Giulia Corte, Melek Yalcin Mutlu, Michael Wolfgang Höner, Ioannis Sagonas, Birte Coppers, Anna-Maria Liphardt, David Simon, Arnd Kleyer, Lukas Folle, Michael Sticherling, Georg Schett, Andreas Maier, Filippo Fagni
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-04-01
Series:	Frontiers in Medicine
Subjects:	psoriasis psoriatic arthritis nail disease NAPSI MNAPSI artificial intelligence
Online Access:	https://www.frontiersin.org/articles/10.3389/fmed.2025.1574413/full
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Advancement and independent validation of a deep learning-based tool for automated scoring of nail psoriasis severity using the modified nail psoriasis severity index

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