Predicting the Future of Aesthetic Surgery: An Artificial Intelligence Framework for Global Publication Forecasting.

BACKGROUND: Artificial intelligence (AI) has transformed clinical decision making, yet its application to forecasting the evolution of surgical science remains underdeveloped. Anticipating future research trajectories represents a critical unmet need for strategic planning, workforce allocation, and innovation stewardship in aesthetic surgery. OBJECTIVES: The aim of this study was to develop and validate an AI-assisted forecasting framework capable of modeling and predicting global aesthetic surgery research activity. METHODS: We performed a population-level observational analysis of all PubMed-indexed aesthetic surgery publications from 2010 to 2024. A fully autonomous AI pipeline conducted large-scale data ingestion, followed by high-fidelity semantic classification of publications by research domain and country (validated accuracy >97%). Annualized outputs were analyzed using optimized exponential-smoothing and autoregressive time-series models to generate long-horizon forecasts with 95% CIs. RESULTS: The framework processed 24,026 records, yielding 23,521 eligible publications across 13 journals. Exponential smoothing demonstrated superior predictive performance (R2 = 0.94, root mean square error = 166.6). Global research output is projected to increase by 21.9% by 2030, reaching 2939 publications annually (95% CI, 2612-3265). Minimally invasive and injectable research exhibited the steepest projected growth (+46.1 publications/year). CONCLUSIONS: This study establishes AI-driven forecasting as a next-generation analytic paradigm for surgical meta-research. By integrating autonomous data ingestion, semantic intelligence, and rigorously validated time-series modeling, the framework operationalizes predictive intelligence-shifting aesthetic surgery research from retrospective surveillance to prospective trajectory mapping. The resulting system is scalable, reproducible, and continuously recalibratable, positioning AI as a strategic instrument for anticipatory research governance, resource allocation, and human-capital planning in surgical science.