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 …

Abstract Purpose of Review Artificial intelligence (AI) is often presented as a transformative
technology for clinical medicine even though the current technology maturity of AI is low. The …

Over the last ten years, the field of dermatology has experienced significant advancements
through the utilization of artificial intelligence (AI) technologies. The adoption of such …

Recent advances in artificial intelligence (AI) in dermatology have demonstrated the
potential to improve the accuracy of skin cancer detection. These capabilities may augment …

Melanoma detection, prognosis, and treatment represent challenging and complex areas of
cutaneous oncology with considerable impact on patient outcomes and healthcare …

The worldwide explosion of interest in artificial intelligence (AI) has created a before-and-
after moment in our lives by generating great improvements in such sectors as the …

Background Artificial intelligence (AI) image recognition models have been relatively
successful in diagnosing cutaneous manifestations in individuals with light skin tone …

Cutaneous squamous cell carcinoma (cSCC) harbors metastatic potential and causes
mortality. However, clinical assessment of metastasis risk is challenging. We approached …

Background Machine learning (ML) has been increasingly utilized for skin cancer screening,
primarily of melanomas but also of non-melanoma skin cancers (NMSC). Objective This …

Abstract Purpose of Review The purpose was to summarize the current role and state of
artificial intelligence and machine learning in the diagnosis and management of melanoma …