Deep learning (DL) has become one of the major approaches in computational
dermatopathology, evidenced by a significant increase in this topic in the current literature …

Primary cutaneous lymphomas (CLs) represent a heterogeneous group of T-cell lymphomas
and B-cell lymphomas that present in the skin without evidence of extracutaneous …

Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …

Artificial intelligence (AI), including deep learning methods that leverage neural network-
based algorithms, hold significant promise for dermatopathology and other areas of …

The current subjective histopathological assessment of cutaneous melanoma is challenging.
The application of image analysis algorithms to histological images may facilitate …

The frequency of basal cell carcinoma (BCC) cases is putting an increasing strain on
dermatopathologists. BCC is the most common type of skin cancer, and its incidence is …

Melanoma is a kind of skin cancer caused by the irregular development of pigment‐
producing cells. Since melanoma detection efficiency is limited to different factors such as …

Simple Summary Melanoma is one of the most common malignancies in the United States.
For the diagnosis of melanoma, histology images are examined by a trained pathologist …

Background Institutes of dermatopathology are faced with considerable challenges
including a continuously rising numbers of submitted specimens and a shortage of …

Predicting labels of gigapixel whole-slide images (WSIs) and localizing regions of interest
(ROIs) with high precision are of great interest in computational pathology. The existing …