Exploring the role of artificial intelligence (AI) in pediatric dermatology for underserved communities in the United States

Skin rashes and lesions are among the most common health concerns in pediatric patients, yet access to pediatric dermatologists remains limited. This shortage contributes to delays in clinical diagnoses, suboptimal treatment, and reduced quality of life for affected patients. Artificial intelligence (AI), particularly image-based diagnostic and decision-support tools, offers a promising approach to augment care delivery in regions where specialist access is scarce. AI has the potential to improve diagnostic accuracy and enhance triage for common pediatric skin conditions. By assisting clinicians in identifying disorders and recommending evidence-based management pathways, AI can reduce the time to intervention. Recent studies have demonstrated that AI can achieve diagnostic accuracy comparable to that of specialists and improve clinician performance when used as a support tool. To ensure these benefits are equitably distributed, however, AI tools must be designed with attention to social determinants of health, including disparities in digital access, bias in algorithm training, and the need for cultural competence. This review examines the current applications of AI in pediatric dermatology, with a focus on its role in rural and primary care settings. It also explores how AI intersects with the social determinants of health and the psychosocial well-being of children, including stigma, mental health, and quality of life. Equitable design and careful implementation will determine whether AI can effectively assist pediatric dermatologic care or exacerbate existing disparities. Our analysis draws on peer-reviewed literature and publicly available AI tools from PubMed and Google Scholar, using Boolean operations.