Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …

Skin cancer is one of the most dangerous diseases in the world. Correctly classifying skin
lesions at an early stage could aid clinical decision-making by providing an accurate …

Background Use of artificial intelligence to identify dermoscopic images has brought major
breakthroughs in recent years to the early diagnosis and early treatment of skin cancer, the …

Deep convolutional neural network (DCNN) models have been widely explored for skin
disease diagnosis and some of them have achieved the diagnostic outcomes comparable or …

This study aims to create a precise skin cancer classification system (SC-CS) able to
distinguish various skin cancer types. Targeted categories include melanoma, vascular …

In clinical applications, neural networks must focus on and highlight the most important parts
of an input image. Soft-Attention mechanism enables a neural network to achieve this goal …

Melanoma is a fatal skin cancer that is curable and has dramatically increasing survival rate
when diagnosed at early stages. Learning-based methods hold significant promise for the …

Iontronic sensors represent a novel class of soft electronics which not only replicate the
biomimetic structures and perception functions of human skin but also simulate the …

Skin lesions are essential for the early detection and management of a number of
dermatological disorders. Learning-based methods for skin lesion analysis have drawn …

Abstract Background and Objective: Medical image classification problems are frequently
constrained by the availability of datasets.“Data augmentation” has come as a data …