Advancements in machine learning (ML) are making artificial intelligence more feasible in dermatology, with promising results for diagnosing skin cancers, though few studies cover common or inflammatory dermatoses. To evaluate the diagnostic accuracy...
Langerhans cell histiocytosis (LCH) is a rare inflammatory myeloid neoplasm characterized by the clonal proliferation of myeloid progenitor cells. The reactivation rate of LCH exceeds 30%. However, an effective prediction model to predict reactivatio...
The correlation between IgE anti-BP180 NC16A autoantibody and disease activity of bullous pemphigoid (BP) remains disputable. To determine the levels of IgE anti-BP180 NC16A autoantibody and its clinical significance in untreated BP patients. IgG and...
Convolutional neural networks are a type of deep learning algorithm. They are mostly applied in visual recognition and can be used for the identification of melanomas. Multiple studies have evaluated the performance of convolutional neural networks, ...
General practitioners (GPs) are playing a key role in skin cancer screening. Non-melanoma skin cancer is frequent and difficult to diagnose. We aimed to assess whether GPs are facing difficulties in diagnosing non-pigmented skin tumours (NPSTs) and w...
Currently, artificial intelligence (AI) heavily impacts all human activities, including medicine, where needs for data analysis and interpretation are high and where technology opens new perspectives. Considering that current treatments do not always...
Diagnosis in dermatology is largely based on contextual factors going far beyond the visual and dermoscopic inspection of a lesion. Diagnostic tools such as the different types of dermoscopy, confocal microscopy and optical coherence tomography (OCT)...