ReviewJournal of cosmetic dermatology2025
Artificial Intelligence in Aesthetic Medicine: Applications, Challenges, and Future Directions.
Review in Journal of cosmetic dermatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled 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.
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
13 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
- A deep learning framework for recognizing skin changes secondary to chronic venous insufficiency in clinical photographs: a multicentre validation study.Annals of medicine · 2026Article
- Review
- Beauty, Bias, and Beyond: The Role of Artificial Intelligence in Aesthetic Medicine.Journal of cosmetic dermatology · 2026Article
- Review
- [Artificial intelligence-based holistic, individualized facial analysis in aesthetic medicine].Dermatologie (Heidelberg, Germany) · 2026Review
- Sociotechnical-systems analysis of IoT-AI convergence in cosmetic health.Frontiers in medicine · 2026Article
- The evolving landscape of eyebrow reconstruction: from traditional flaps to minimally invasive techniques and regenerative medicine.Frontiers in surgery · 2026Review
- Accuracy, readability, and bias of GPT-4o mini responses to oculoplastic patient questions.Frontiers in ophthalmology · 2026Article
- A Narrative Review of Evolving Techniques in Nonsurgical Rhinoplasty: Risk Profile and Clinical Outcomes of Fillers.Cureus · 2026Review
- Introducing biofeedback-integrated laser therapy: a novel approach for enhancing scar treatment.Lasers in medical science · 2025Article
- Reliability of Large Language Model-Based Chatbots Versus Clinicians as Sources of Information on Orthodontics: A Comparative Analysis.Dentistry journal · 2025Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial Intelligence (AI) is transforming healthcare by enhancing diagnostics, treatment personalization, and operational efficiency. In aesthetic medicine-a field blending medical expertise with artistic judgment-AI is increasingly being used to improve precision, optimize treatment outcomes, and personalize patient care. However, its integration presents both opportunities and ethical challenges, necessitating a critical evaluation of its role in this evolving field.
objectiveThis study examines AI's applications in aesthetic medicine, focusing on its role in facial analysis, robotic-assisted procedures, predictive patient outcome modeling, and personalized treatment planning. Additionally, it explores ethical concerns, algorithmic biases, data privacy issues, and regulatory challenges affecting AI adoption in aesthetic practices.
methodsA comprehensive review of AI-driven technologies in aesthetic medicine was conducted, analyzing literature on machine learning (ML), deep learning, and computer vision applications. Case studies on AI-assisted facial symmetry analysis, robotic hair transplantation, and predictive analytics in patient care were examined to evaluate AI's effectiveness and limitations.
resultsAI enhances aesthetic procedures by improving diagnostic accuracy, offering virtual simulations of treatment outcomes, and enabling hyper-personalized treatment plans based on patient data. AI-driven chatbots and virtual assistants streamline patient interactions, while robotic systems assist in precision-based tasks such as laser treatments and hair restoration. However, challenges such as biased training data, lack of transparency in AI decision-making, and inconsistencies in regulatory approvals hinder widespread adoption. The integration of AI in aesthetic medicine presents a paradigm shift from traditional approaches to data-driven, personalized interventions. However, ethical concerns such as data privacy, informed consent, and algorithmic fairness must be addressed. Overreliance on AI may diminish the human-centric approach essential in aesthetic procedures, where patient expectations and subjective perceptions of beauty play a crucial role. Collaboration between technologists, clinicians, and policymakers is necessary to develop standardized AI guidelines that ensure fairness, safety, and efficacy.
conclusionAI has the potential to revolutionize aesthetic medicine by improving precision, efficiency, and patient satisfaction. However, its successful implementation requires balancing technological advancements with ethical considerations and regulatory frameworks. Future research should focus on integrating AI with emerging technologies such as augmented reality (AR) and genomic-based personalization to enhance aesthetic outcomes while maintaining transparency and patient trust.
Indexed as
Identifiers
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.