Evidence map›Paper›PMID 42141211›Full record

SynthesisAesthetic plastic surgery2026

Technological Integration in Aesthetic Practice: A Systematic Review of Artificial Intelligence, Augmented Reality and Robotics in Cosmetic Procedures.

Raffaele Aguglia, Tobias Niederegger, Yannick Sprunger, Leonard Knoedler, Javier Gonzalez, Curtis L Cetrulo, Alexandre G Lellouch, Diala Haykal

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis 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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Raffaele AgugliaDivision of Plastic and Reconstructive Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA. raffaeleagugliaprs@gmail.com.ORCID http://orcid.org/0009-0007-1266-3409
Tobias NiedereggerUniversity of Heidelberg, Medical Faculty, Heidelberg, Germany.
Yannick SprungerPlastic and Reconstructive Surgery Department, Hôpital Européen Georges Pompidou, Paris, France.
Leonard KnoedlerDivision of Plastic and Reconstructive Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Javier GonzalezDivision of Plastic and Reconstructive Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Curtis L CetruloDivision of Plastic and Reconstructive Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Alexandre G LellouchDivision of Plastic and Reconstructive Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Diala HaykalCentre Laser Palaiseau, Palaiseau, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI), augmented reality (AR), and robotics are rapidly transforming aesthetic practice. Despite their growing integration, evidence on their clinical applications, performance, and challenges in cosmetic procedures remain fragmented. This study systematically reviews clinical applications of these tools.

methodsA systematic review was conducted following PRISMA 2020 guidelines and registered in PROSPERO (CRD420251077168). Comprehensive searches of PubMed/MEDLINE, EMBASE, Web of Science, and Google Scholar identified original studies on AI, AR, or robotics in aesthetic procedures. Eligible studies included applications in surgical and non-surgical contexts.

resultsFrom 12,316 screened studies, 55 (0.5%) met the eligibility criteria, published between 2009 and 2025. Most studies (n = 33, 60%) applied AI-based image analysis, enabling objective quantification of skin features, volumetric planning in breast and facial surgery, and improved patient communication. A smaller proportion (n = 5, 9.1%) focused on AI-driven risk assessment and outcome prediction. Robotics (n = 9, 16%) could enhance precision in facial, mandibular, hair, and laser procedures, and outperform manual techniques. AR (n = 8, 15%) allowed intraoperative navigation, and preoperative simulations. Methodological quality was overall low-to-moderate.

conclusionWhile AI is rapidly advancing, offering software capable of comprehensive skin analysis, improving patient selection, predicting outcomes, and aiming to objectively assess the results of aesthetic procedures, AR and robotics have been slower to gain a foothold in cosmetic medicine and surgery. Although some studies highlight the remarkable potential of these technologies, their integration into routine practice remains hindered by limitations in evidence quality, dataset diversity, workflow adaptability, cost, and ethical oversight. NO LEVEL ASSIGNED: This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. 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 .

Indexed as

Artificial IntelligenceAugmented RealityCosmetic TechniquesRoboticsEstheticsHumansAesthetic medicineArtificial intelligenceAugmented realityCosmetic proceduresCosmetic surgeryOutcome simulationRobotics

Identifiers

PMID42141211
PMCPMC13433551

What OpenQuestion holds

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Registered trials

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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.