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A dual track predictive model for assessing crow's feet aging across different clinical severity grades
Qitian Fu1,2, Yuqing Han1,2, Jiaqi Zhang1,2
1Department of Cosmetics, School of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, China.
Scientific Reports
|June 20, 2026
Summary
Objective skin aging assessment is improved by a new dual-track model for crow's feet. This framework uses machine learning to translate facial measurements into clinical scores, enhancing accuracy.
Area of Science:
- Dermatology and biomedical engineering focused on skin aging.
- Computational modeling and machine learning applications in clinical assessment.
Background:
- Current crow's feet assessment relies on subjective scales and limited objective tools, hindering standardization.
- Understanding the micro-physiological basis of aging skin, specifically crow's feet, is crucial for objective evaluation.
Purpose of the Study:
- To develop an objective, standardized, and stage-specific predictive framework for crow's feet severity.
- To correlate macroscopic facial parameters with clinical grading using advanced modeling techniques.
- To elucidate the microstructural changes associated with different stages of crow's feet development.
Main Methods:
- Recruited 350 healthy Chinese women for data acquisition.
- Utilized VISIA-CR, DermaTOP®, and two-photon microscopy for macroscopic and microstructural parameter collection.
- Developed a dual-track modeling strategy combining Ridge Regression and TPOT-optimized Support Vector Regression (SVR), validated with SHapley Additive exPlanations (SHAP).
Main Results:
- Crow's feet severity demonstrated a non-linear increase with age.
- Two-photon microscopy supported distinct epidermal and dermal changes at higher crow's feet grades (4 and 5).
- A Stacked SVR model excelled in early stages (Grades 0-2), while Ridge Regression proved robust for later stages (Grades 3-4), with an overall R² of 0.519 for Ridge Regression.
Conclusions:
- The study establishes a stage-specific dual-track predictive framework for objective crow's feet assessment.
- Clarified the micro-physiological basis of crow's feet aging, linking visual signs to cellular changes.
- Provides a more objective and standardized approach to evaluating skin aging, overcoming limitations of current methods.
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