Deep learning models are efficient in learning the features that assist in understanding
complex patterns precisely. This study proposed a computerized process of classifying skin …

Efficient methods developed with deep learning in the last ten years have provided
objectivity and high accuracy in the diagnosis of skin diseases. They also support accurate …

Dermatological disorders are one of the most widespread diseases in the world. Despite
being common its diagnosis is extremely difficult because of its complexities of skin tone …

Skin problems are among the most common ailments on Earth. Despite its popularity,
assessing it is not easy because of the complexities in skin tones, hair colors, and hairstyles …

Skin cancer is an emerging global health problem with 123,000 melanoma and 3,000,000
non-melanoma cases worldwide each year. The recent studies have reported excessive …

Propensity of skin diseases to manifest in a variety of forms, lack and maldistribution of
qualified dermatologists, and exigency of timely and accurate diagnosis call for automated …

Background: Numerous studies have attempted to apply artificial intelligence (AI) in the
dermatological field, mainly on the classification and segmentation of various dermatoses …

The MobileNet model was used by applying transfer learning on the 7 skin diseases to
create a skin disease classification system on Android application. The proponents gathered …

Background The emergence of the deep convolutional neural network (CNN) greatly
improves the quality of computer-aided supporting systems. However, due to the challenges …

Skin lesion detection and analysis are very important because skin cancer must be found in
its early stages and treated immediately. Once installed in the body, skin cancer can easily …