Simple Summary The proposed research aims to provide a deep insight into the deep
learning and machine learning techniques used for diagnosing skin cancer. While …

In this paper, we first describe the basics of the field of cancer diagnosis, which includes
steps of cancer diagnosis followed by the typical classification methods used by doctors …

In this paper, we aim to provide a survey on the applications of deep learning for cancer
detection and diagnosis and hope to provide an overview of the progress in this field. In the …

Melanoma is the most aggressive type of skin cancer, which significantly reduces the life
expectancy. Early detection of melanoma can reduce the morbidity and mortality associated …

Abstract Background and Objectives Artificial intelligence (AI) models trained on multi-
centric and multi-device studies can provide more robust insights and research findings …

Color medical images introduce an additional confounding factor compared to conventional
grayscale medical images: color variability. This variability can lead to inconsistent …

Background and objectives Because skin cancer affects millions of people worldwide,
computational methods for the segmentation of pigmented skin lesions in images have been …

Melanoma spreads through metastasis, and therefore, it has been proved to be very fatal.
Statistical evidence has revealed that the majority of deaths resulting from skin cancer are as …

Background and objective Dermatological images are typically diagnosed based on visual
analysis of the skin lesion acquired using a dermoscope. However, the final quality of the …

Convolutional neural networks have been effective in several applications, arising as a
promising supporting tool in a relevant Dermatology problem: skin cancer diagnosis …