ReviewAesthetic plastic surgery2026
Artificial Intelligence in Non-Surgical Cosmetic Procedures: A Multi-Stakeholder Revolution.
Review in Aesthetic plastic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-surgical cosmetic procedures have experienced significant growth, driven by advancements in technology and changing consumer demographics. The global non-surgical aesthetic market is projected to reach $90.2 billion by 2030, with Asia, particularly China, being a major contributor. Artificial Intelligence (AI) is revolutionizing these procedures by enhancing patient engagement, clinical decision-making, and operational efficiency. AI applications span from personalized aesthetic assessments and treatment planning to real-time monitoring and post-procedural care. This review synthesizes recent advancements in AI integration across the non-surgical cosmetic workflow, addressing challenges such as data privacy, algorithmic bias, and the need for comprehensive physician training. By adopting a multi-stakeholder perspective, the review highlights AI's potential to democratize access to personalized, safe aesthetic care while emphasizing the importance of ethical considerations and regulatory frameworks.Level of Evidence IV This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.