ISSN 2979-8116 (Online) · Online-only · Published Monthly

    Aesthetic Intelligence

    A peer-reviewed journal of aesthetic medicine, published by the Harley Street Institute

    Social preview card for Artificial Intelligence in Aesthetic Medicine: Current Applications and Future Directions

    Review Article

    Artificial Intelligence in Aesthetic Medicine: Current Applications and Future Directions

    Dr. Ahmed Haq1

    1. 1 Harley Street Institute, London, United Kingdom

    Corresponding author: journal@harleystreetinstitute.com

    Journal: Aesthet Intell

    DOI: to be assigned

    Volume / Issue: 1 / 4

    Pages: 1–14

    Received: 2025-08-12

    Accepted: 2025-09-30

    Published: 2026-05-05

    Licence: CC BY 4.0

    Abstract

    Background.
    Artificial intelligence (AI) is increasingly integrated into aesthetic medicine for diagnostics, treatment planning, image analysis and patient communication. The pace of clinical adoption now exceeds the rate of formal evaluation.
    Methods.
    A narrative review of peer-reviewed literature (2018–2025) was conducted using PubMed, Embase and Cochrane databases. Studies addressing machine learning, deep learning and large language models in aesthetic and dermatological practice were included.
    Results.
    AI is used in skin analysis, complication prediction, injectable planning, photographic standardisation and chatbot-based patient education. Most reported tools demonstrate technical feasibility, but high-quality clinical validation studies remain limited.
    Conclusion.
    AI offers meaningful adjunctive value in aesthetic medicine but cannot replace clinical reasoning. Standardised evaluation frameworks and transparent disclosure are required before widespread integration.

    Keywords: artificial intelligence, aesthetic medicine, machine learning, skin analysis, patient safety, clinical decision support

    1. Introduction

    Artificial intelligence has moved from an academic curiosity to a clinical tool within aesthetic medicine. This review summarises current applications, examines the evidence base, and discusses regulatory and ethical considerations relevant to clinicians.

    2. Current Clinical Applications

    AI applications in aesthetic medicine fall into four broad categories: diagnostic image analysis, treatment planning, complication prediction, and patient-facing communication tools.

    Image analysis algorithms can quantify pigmentation, vascularity, wrinkles and pore size with reproducibility approaching that of expert clinicians.

    3. Evidence and Limitations

    The majority of published studies report on tool development rather than clinical outcomes. Few have evaluated whether AI integration improves patient safety, satisfaction, or efficiency in real-world practice.

    4. Future Directions

    Future work should prioritise prospective clinical trials, transparent training-data disclosure, and integration of AI tools within accredited educational pathways.

    5. Conclusion

    AI is a powerful adjunct in aesthetic medicine. Responsible integration requires clinical validation, transparent disclosure, and ongoing education.

    AI Disclosure

    Large language model assistance was used in literature triage and manuscript drafting. The named human author retains full responsibility for the accuracy, integrity and editorial content of this work.

    Competing Interests

    The author(s) declare no competing financial or non-financial interests relevant to this work.

    Funding

    This work received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

    Ethics & Consent

    Where applicable, ethical approval and informed patient consent were obtained in accordance with the Declaration of Helsinki. Reviews and commentaries did not require ethical approval.

    References

    1. Esteva A, Kuprel B, Novoa RA, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017;542(7639):115–118.
    2. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25(1):44–56.
    3. Liopyris K, Gregoriou S, Dias J, et al. Artificial Intelligence in Dermatology: Challenges and Perspectives. Dermatol Ther (Heidelb). 2022;12(12):2637–2651.
    4. Du-Harpur X, Watt FM, Luscombe NM, et al. What is AI? Applications of artificial intelligence to dermatology. Br J Dermatol. 2020;183(3):423–430.
    5. Kumar Y, Koul A, Singla R, et al. Artificial intelligence in disease diagnosis: a systematic literature review. J Ambient Intell Humaniz Comput. 2023;14:8459–8486.

    © 2026 Harley Street Institute. Published under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0).

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    Editorial Masthead

    Aesthetic Intelligence

    A peer-reviewed journal of aesthetic medicine, published by the Harley Street Institute

    Publisher
    Harley Street Institute
    8-10 Harley Street, London W1G 9QD, United Kingdom
    Format & Frequency
    Online-only · Published Monthly
    Established 2026
    Editor-in-Chief
    Dr Hena Haq
    Peer Review
    Single-blind external peer review by at least two reviewers for original research and review articles; editorial review for commentary and editorial content.
    Editorial Office
    Editorial Office, Aesthetic Intelligence, Harley Street Institute, 8-10 Harley Street, London W1G 9QD, United Kingdom
    journal@harleystreetinstitute.com
    License
    Articles are published under a Creative Commons Attribution 4.0 International License (CC BY 4.0) unless otherwise stated. Authors retain copyright.
    ISSN (Online)
    ISSN 2979-8116 (Online)The International Standard Serial Number (ISSN) is the official identifier assigned by the ISSN UK Centre at the British Library. It confirms Aesthetic Intelligence is a catalogued, citable serial publication of record, indexed in the global ISSN Register and recognised by libraries, abstracting services and indexers worldwide.
    Indexing
    Applications planned with DOAJ, Crossref, PubMed Central and Scopus during Volume 1 (2026). The journal follows a monthly publication model (one issue per calendar month) with sequential issue numbering within each volume.