Comprehensive and diverse datasets, including rare and precancerous lesions, are needed for skin cancer diagnosis and treatment with artificial intelligence, according to a study recently published in Healthcare Analytics. Although research has been published on artificial intelligence applications in skin cancer, there is an unmet need for specialized healthcare professionals, as well as rapid advancements in automated diagnosis and treatment methods. Eman Rezk, MD, and colleagues conducted a comprehensive review employing text mining to identify key themes of artificial intelligence in skin cancer diagnosis and treatment research. Despite the identified knowledge gaps identified in the analysis, AI can significantly improve patient outcomes through early diagnosis, lesion management, treatment option recommendation, disease recurrence prediction, and tumor excision.