The letters “Interpretation of the Outputs of Deep Learning Model trained with Skin Cancer
Dataset” and “Automated Dermatological Diagnosis: Hype or Reality?” highlight the …

Among the most prevalent disorders is skin infection. Clinical manifestations are difficult to
classify because to various diverse classifications, the similarity of various clinical signs, and …

In the last few years, a great attention was paid to the deep learning Techniques used for
image analysis because of their ability to use machine learning techniques to transform …

Convolutional Neural Networks (CNNs) have the potential to assist medical doctors in
diagnosis and treatment stage. This paper has been prepared to help dermatologists by …

In this paper, a deep neural network based ensemble method is experimented for automatic
identification of skin disease from dermoscopic images. The developed algorithm is applied …

Skin cancer is among the primary cancer types that manifest due to various dermatological
disorders, which may be further classified into several types based on morphological …

Recently, there has been great interest in developing Artificial Intelligence (AI) enabled
computer-aided diagnostics solutions for the diagnosis of skin cancer. With the increasing …

Detecting skin disorders just through visual inspection is difficult due to the complicated and
overlapping nature of sick lesions, background skin textures, skin hair, low illumination, etc …

Convolutional Neural Networks allows prediction and automation of various tasks in
interdisciplinary fields. These models have the ability to learn various features from image …

Simple Summary According to skin disease reports by healthcare organizations, the number
of cases of skin disease is growing gradually over the years globally. In skin disease …