Evidence map›Paper›PMID 42422339›Full record

ReviewAesthetic surgery journal. Open forum2026

The Impact of Artificial Intelligence on Facial Aesthetic Surgery: A Systematic Review.

Aurelia-Alexandra Colceriu, Petru-Iulian Ifteni, Liliana Rogozea, Florin-Gabriel Leașu, David Stuckler

Abstract readReview
In one paragraph

Review in Aesthetic surgery journal. Open forum, 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

5 authors.

Petru-Iulian Ifteni
Liliana Rogozea
Florin-Gabriel Leașu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) has transformed medical practice, with early adopters using custom models in imaging-heavy fields. Millions of cosmetic surgeries prompt surgeons to seek better tools amid pressure for ideal outcomes. Past reviews have covered AI in facial cosmetic surgery for both reconstructive and aesthetic purposes. There remains a need to cover AI applications in a wider range of specialties while assessing clinical relevance, readiness, and, when available, comparison with standard care. This research examines AI's impact on facial cosmetic surgery by reviewing patient care stages, surgery types, AI architectures, and model sourcing. Following PRISMA 2020 guidelines and PROSPERO registration, the authors searched PubMed and Web of Science on August 25, 2025, for English studies on facial aesthetic surgery. They included studies using AI across all care stages, with at least 4 patients. Two reviewers independently screened, assessed, and extracted data. Of 1832 records, 29 met criteria. The authors used the Cochrane ROBINS-I and RoB 2 tools for risk of bias assessment. Most studies, mainly in Asia or the United States, focus on AI tool validation, development, and applicability, with few interventional studies. Most AI models use convolutional neural networks and are commercially available. In facial aesthetic surgery, AI aids treatment planning and outcome assessment, especially in facelifts, rhinoplasty, and blepharoplasty. The results highlight AI's potential and emphasize the need for standardized reporting, updated regulations, and education programs that promote collaboration where surgeons co-design AI models.

Identifiers

PMID42422339
PMCPMC13345743

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.