AI Footprint Grows in Aesthetic Surgery: Analysis

Key Takeaways

• Researchers conducted a review of 460 original studies evaluating artificial intelligence (AI) applications in plastic surgery across patient education, diagnosis, clinical decision-making, and practice management.

• Machine-learning and deep-learning systems predominated in diagnostic applications, while large language models (LLMs) were most commonly used for patient education.

• Heterogeneity in study design, AI modality, and endpoints limits cross-study comparisons and clinical generalizability.

Artificial intelligence (AI) is increasingly embedded in plastic surgery, according to a narrative review published in Aesthetic Surgery Journal.

Authors used PubMed searches of articles published before September 22, 2025, identifying 1,866 records related to AI in plastic surgery. After excluding letters, commentaries, reviews, surveys, and non–English-language articles, 460 studies met inclusion criteria.¹ Studies were categorized by AI modality, clinical application, and subspecialty, with some articles assigned to multiple categories.

Among the qualifying studies, 133 focused on diagnosis, 79 on clinical decision-making, 62 on outcome prediction or risk assessment, and 46 on clinical outcome assessment. AI was also applied to patient education (54 studies), plastic surgeon education (35 studies), practice management (46), and research (17). In terms of modality, 299 studies evaluated machine-learning or deep-learning systems, 155 used large language models, 9 incorporated text-to-imaging models, and 6 used natural language processing tools. LLMs were most frequently studied in patient education contexts, whereas machine learning predominated in diagnostic applications.

Methodologies and endpoints varied widely, limiting standardization and direct comparison across studies. The review underscores that although AI applications now span the breadth of plastic surgery, the literature remains heterogeneous and methodologically inconsistent.

"Plastic surgeons must know the advantages and opportunities provided by AI, while recognizing its limitations, pitfalls, and areas needing improvement," the authors wrote. "Ethical, safe, and forward-thinking AI in plastic surgery requires a multidisciplinary approach involving plastic surgeons, data scientists, ethicists, legal experts, and policymakers."

Source: Copeland-Halperin L. Aesthetic Surgery Journal. 2026. doi:10.1093/asj/sjaf239