Skin Cancer Detection Using Artificial Intelligence: Enhancing Accuracy In Melanoma Diagnosis

Malignant melanoma is an aggressive cancer originating from melanocytes with high metastatic potential which confers an ominous prognosis.As useful as the traditional diagnostic methods which are visual inspection and dermoscopy which are nonetheless subjective and require a lot of expertise.In this paper, applications of artificial intelligence (AI) in the diagnosis of melanomas are discussed, outlining ways in which AI, and specifically machine learning and deep learning algorithms in melanoma detection, can ameliorate shortcomings associated with traditional approaches.AI systems generate more accurate and consistent diagnosis based on an analysis of large dataset of skin images attuned to data derived from dermatological practice.In this regard, this manuscript aims at reviewing existing literature of AI-based applications in melanoma detection, assessing their strengths and weaknesses for melanoma detection via the perspective of clinical impact, and striving to demonstrate the overwhelming potential of AI to change the approach towards skin cancer diagnostics.