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Predicting Age-Related Facial Hyperpigmentation via Dermatologist Knowledge Elicitation and Generative Modeling
Edouard Raynaud1,2, Laudine Bertrand3, Frederic Flament3
1Bioclinical Research Center (CRB) of L'Oréal Advanced Research, Saint-Louis Hospital, Paris, France.
Introduction:
Facial hyperpigmentation is a primary marker of skin aging in Asian populations. While many artificial intelligence (AI)-based aging simulators exist on social media, they often lack scientific transparency and dermatological validation. This study introduces and validates a novel facial aging simulator specifically engineered to provide personalized, evidence-based predictions of pigmentary spot progression according to varying levels of ultraviolet (UV) exposure and photoprotection.
Methods:
The simulator utilizes a dual-tool framework: Elicitation Based Aging Simulator (EBAS) and AgingMapGAN (AMGAN). EBAS leverages the collective expertise of 28 dermatologists via a structured Delphi process and causal Bayesian belief networks (BBNs) to model skin aging trajectories. AMGAN, a conditional generative adversarial network, provides high-resolution visual representations of these trajectories. The model was trained on a standardized dataset of 600 individuals and focused on the density of pigmentary spots (DPS) on the cheek. Model performance was benchmarked against expert clinical grading using correlation metrics.
Results:
The simulator demonstrated high accuracy in replicating expert logic (Pearson's correlation 0.96). In a case study of a 38-year-old female of Chinese descent, the model predicted the 15-year probability of a clinically significant progression (a two-grade increase in DPS). In the absence of photoprotection, the probability of reaching this elevated grade by age 53 was 71.35%, whereas regular daily application of SPF 50+ sunscreen reduced this probability to 39.24%.
Conclusions:
This framework represents the application of a scientifically validated image-generation tool for predicting age-related hyperpigmentation based on individual exposome factors. By integrating dermatological knowledge, this simulator provides a robust educational and research resource for personalized skincare strategies. The findings confirm that consistent photoprotection significantly mitigates the 15-year trajectory of premature facial aging, offering a scientifically validated foundation for public health communication on prevention.
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