Publications by authors named "A Enk"

Importance: Deep learning convolutional neural networks (DL-CNN) achieved diagnostic accuracies comparable to dermatologists in controlled test environments. However, their performance in diagnosing rare skin tumors (RST) remains unclear. This study aimed to evaluate a binary DL-CNN's diagnostic performance in RST and assess the level of support for an international group of dermatologists.

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Importance: Early detection of cutaneous melanoma (CM) is crucial for patient survival, yet avoiding overdiagnosis remains essential. Differentiating CM from benign melanoma simulators (MelSim) is challenging due to overlapping features. Deep learning convolutional neural networks (DL-CNNs) have demonstrated dermatologist-level accuracy in identifying CM.

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Background: There are only limited histomorphological data on the response of psoriatic skin lesions to topical dithranol. In vivo reflectance confocal microscopy (RCM) in psoriatic skin is highly correlated with histopathological findings and allows non-invasive monitoring of treatment effects on a cellular level.

Patients And Methods: Prospective, single-center pilot study at a university-based clinic of dermatology between January 1 and August 30, 2016.

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T follicular helper (Tfh) cells were recently described as a key cell population for the induction of antibody responses, suggesting their crucial role in bullous pemphigoid pathophysiology. However, functional evidence is missing. In this study, we demonstrate that regulatory T cell-deficient scurfy mice, which spontaneously develop skin disease, including human bullous pemphigoid-like characteristics, show highly increased Tfh cell frequencies.

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