Artificial Intelligence-Driven Skin Aging Simulation as a Novel Skin Cancer Prevention

Area of Science:

• Dermatology
• Public Health
• Artificial Intelligence

Background:

• Skin cancer is a global health concern, with rising incidence rates, particularly among fair-skinned individuals.
• Ultraviolet (UV) radiation is a primary risk factor, yet intentional tanning and sunburns remain prevalent.
• Targeted prevention campaigns are crucial for improving sun protection behaviors, especially in younger demographics.

Purpose of the Study:

• To investigate the efficacy of AI-based facial skin aging simulations in enhancing sun protection behaviors among female adults.
• To assess the short-term and long-term impact of AI-driven visual feedback on UV exposure reduction and protection intensification.

Main Methods:

• A prospective, observational pilot study involving 60 healthy young females.
• Photographs were taken using a VISIA-CR camera, followed by AI-based simulation of facial aging to 80 years.
• Pre- and post-intervention questionnaires assessed sociodemographic data, tanning, and sun protection behaviors, with a 2-year follow-up.

Main Results:

• Participants rated the importance of sun protection significantly higher post-simulation (p < 0.0001).
• 91.7% were motivated to reduce UV exposure and increase protection, perceiving higher individual risk (p < 0.001).
• Long-term follow-up (2 years) showed sustained UV exposure reduction (96%) and increased preference for SPF 50+ sunscreen (60%).

Conclusions:

• AI-assisted photoaging interventions effectively enhance motivation for UV protection in both the short and long term.
• Personalized, generation-specific campaigns using visual AI support can improve cancer-preventative behavior intent.
• The study highlights the potential of AI in public health interventions for skin cancer prevention.