Unveiling the Spectrum of UV-Induced DNA Damage in Melanoma: Insights from AI-Based Analysis of Environmental Factors, Repair Mechanisms, and Skin Pigment Interactions

Melanoma, a global health concern, undergoes a transformative shift in early diagnosis through the integration of artificial intelligence (AI) and environmental factors. Exposure to UVB is the main cause of DNA deterioration in skin cells. The DNA molecules absorb UVB photons, which causes the creation of photoproducts such as pyrimidine (6-4), pyrimidone photoproducts (6-4PPS), and cyclobutane pyrimidine dimers (CPDs). These photoproducts alter important genes, including those that control cell development and apoptosis. These genetic changes accumulate over time as a result of UV-induced DNA damage to melanocytes, turning normal cells into malignant melanoma cells. This study explores the incorporation of ultraviolet (UV) radiation, DNA damage, UV signature mutations, skin pigmentation, melanin biochemistry, and gene-environment interactions into AI-powered melanoma identification systems. The analysis highlights the importance of these factors, contributing to the intricacies of melanoma and emphasizing their critical inclusion in predictive models. Design goals for AI systems prioritize accuracy, customization, comprehensibility, and ethical adherence. AI emerges as a potent ally in reshaping public health initiatives, identifying high-risk areas and populations, redefining early detection, and preventing melanoma on a population-wide scale. The increased incidence of melanoma cases globally can be attributed to overexposure to ultraviolet (UV) radiation. As a significant risk component, this environmental factor is responsible for the startling increase in melanoma incidence that has been occurring since the mid-1960s. The digital dermoscopy in conjunction with AI and environmental factors has demonstrated potential to support early melanoma detection. This study underscores the potential of AI to revolutionize melanoma research, leveraging insights from UV radiation, DNA damage, UV signature mutations, skin pigmentation, melanin biochemistry, and their interactions for enhanced diagnostic capabilities and improved public health outcomes.