ArticleAesthetic plastic surgery2025
An Artificial Intelligence Tool Used for Patient Selection in Cosmetic Surgery.
Article in Aesthetic plastic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Technological Integration in Aesthetic Practice: A Systematic Review of Artificial Intelligence, Augmented Reality and Robotics in Cosmetic Procedures.Aesthetic plastic surgery · 2026Pooled it
- Artificial intelligence-enabled clinical decision support systems in preadmission testing: a scoping review of risk prediction, triage, and perioperative workflows (2020-2025).Journal of clinical monitoring and computing · 2026Article
- Applicability of Complementary Colors in Skin Tone Correction for Young Chinese Adults Based on Image Processing and Machine Learning.Journal of cosmetic dermatology · 2025Article
- BREAST AI-PLAN: Prompt-Driven AI Assistance for Breast Surgery Planning - A Retrospective Single-center Study.In vivo (Athens, Greece)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundCosmetic surgery is becoming increasingly popular, but not all patients are suitable candidates. A thorough preoperative assessment and careful patient selection are essential for achieving successful outcomes. Given the challenges plastic surgeons face in conducting psychological assessments, we believe that artificial intelligence (AI) has the potential to assist in this critical task of patient selection.
methodsBased on previous research findings and the expertise of six senior plastic surgeons, we developed an AI-based patient selection tool using the XGBoost algorithm. We then enrolled 37 patients, who were independently evaluated by both the AI system and two senior plastic surgeons. This clinical validation process was designed to assess the accuracy and reliability of the AI tool in identifying suitable candidates for cosmetic surgery.
resultsClinical validation with 37 patients demonstrated a high level of agreement between the AI system and the surgeons in patient assessment and selection. Both the AI and the surgeons agreed that 73% of patients were suitable for surgery, while 27% were not. Quantitatively, there was a strong positive correlation between the AI and the surgeons' assessments, with correlations of r = 0.907 (95% CI = [0.837, 0.949], p < 0.001) for the average surgeon rating, r = 0.909 (95% CI = [0.824, 0.955], p < 0.001) for Surgeon A, and r = 0.879 (95% CI = [0.798, 0.930], p < 0.001) for Surgeon B.
conclusionWe've developed the first smartphone-based AI tool designed to evaluate patients prior to cosmetic surgery. This practical tool enables surgeons to make wise and effective patient selection. The AI tool demonstrated strong performance in our clinical validation. 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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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.