ABSTRACT
Skin cancer represents one of the most prevalent and preventable forms of cancer worldwide, yet its incidence continues to rise due to environmental, genetic, and behavioral factors. This chapter explores the biological, clinical, and epidemiological dimensions of skin cancer while emphasizing diagnostic complexities and the transformative potential of artificial intelligence (AI). It discusses the two major forms—melanoma and non-melanoma skin cancers (NMSCs)—alongside their clinical manifestations, risk factors, and molecular mechanisms. Traditional diagnostic techniques such as dermoscopy and histopathology, though effective, remain limited by subjectivity and invasiveness. The chapter establishes the theoretical foundation for AI integration in dermatology by linking biological structures, lesion morphology, and molecular pathways with computational analysis. Through this interdisciplinary approach, it underlines how AI-driven tools can enhance accuracy, accessibility, and early detection, thereby reducing the global burden of skin cancer.
