Research

Grounded in rigorous science, we continuously publish cutting-edge research, while our technology is widely validated and published by leading researchers and clinical institutions worldwide.

2026 SID Conference

Society for Investigative Dermatology

Prediction of skin biophysical parameters from facial images using deep learning in large-scale population cohorts

Using ~6,000 participants across three independent cohorts, we developed and externally validated machine learning models to predict multidimensional skin phenotypes from facial images.

2025 JID Journal

Journal of Investigative Dermatology

GWASs of the Nasolabial Fold Identified Variants Related to Genes that Also Affect Facial Morphology

The nasolabial fold (NLF) is a prominent dermatological phenotype of the aging midface. Previous anatomical studies have clarified that the NLF is potentially induced by the aging changes in the superficial musculoaponeurotic system architecture, cutaneous ligament, midface musculature and fat compartments, and craniofacial skeleton.

2022 SID Conference

Society for Investigative Dermatology

Genome-wide association study of the nasolabial fold identified novel variants associated with facial morphology (2022)

This preliminary genome-wide association study explores the genetic basis of nasolabial fold variation, identifying candidate loci associated with fold depth and morphology. The findings lay groundwork for understanding how genetic factors influence visible facial aging and support the development of genetically informed skincare solutions.

2022 ISBS Conference

International Society for Biophysics and Imaging of the Skin

Quantifying facial skin aging signs by deep learning-based algorithm (2022)

Deep learning methods for quantifying facial skin aging signs from standardized images.