AI-augmented differential diagnosis of granulomatous rosacea and lupus miliaris disseminatus faciei: A 23-year retrospective pilot study.

ABSTRACT: Granulomatous rosacea (GR) and lupus miliaris disseminatus faciei (LMDF) exhibit overlapping clinical features, making their differentiation challenging. While histopathological examination remains the gold standard, it is invasive and time-consuming, highlighting the need for non-invasive diagnostic approaches. This study evaluates artificial intelligence (AI)-based models for differentiating between GR and LMDF and assess their impact on clinician performance. This retrospective pilot study included 96 patients (62 GR, 34 LMDF) with histopathologically confirmed diagnoses. Neural network models, including convolutional neural networks and vision transformers (ViT), were applied to cropped lesion images while a transformer-based multiple instance learning (TransMIL) approach was used for

SUBMITTER: Lee SH 

PROVIDER: S-EPMC12208491 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature