OBJECTIVE: Computerized analysis of pigmented skin lesions (PSLs) is an active area of
research that dates back over 25years. One of its main goals is to develop reliable automatic …

Dermoscopy is an in vivo method for the early diagnosis of malignant melanoma and the
differential diagnosis of pigmented lesions of the skin. It has been shown to increase …

Importance Convolutional neural networks (CNNs) achieve expert-level accuracy in the
diagnosis of pigmented melanocytic lesions. However, the most common types of skin …

While convolutional neural networks (CNNs) have successfully been applied for skin lesion
classification, previous studies have generally considered only a single clinical/macroscopic …

Background Computer vision may aid in melanoma detection. Objective We sought to
compare melanoma diagnostic accuracy of computer algorithms to dermatologists using …

Artificial Intelligence (AI) is progressively permeating medicine, notably in the realm of
assisted diagnosis. However, the traditional unimodal AI models, reliant on large volumes of …

Background Recent years have been witnessing a substantial improvement in the accuracy
of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on …

The skin is the largest organ in human body. Around 30%-70% of individuals worldwide
have skin related health problems, for whom effective and efficient diagnosis is necessary …

Importance The recent advances in the field of machine learning have raised expectations
that computer-aided diagnosis will become the standard for the diagnosis of melanoma …

The principal objective of screening individuals at risk for melanoma is detection of
cutaneous melanoma during the curable stages of its early evolution. Unaided visual …