Scholarlink

Background <p>Artificial 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.</p> Methods <p>A 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.</p> Results <p>From 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.</p> Conclusion <p>While 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.</p> No Level Assigned <p>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 <a href="http://www.springer.com/00266">www.springer.com/00266</a>.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月15日

查看全文
  • Raffaele Aguglia,
  • Tobias Niederegger,
  • Yannick Sprunger,
  • Leonard Knoedler,
  • Javier Gonzalez,
  • Curtis L. Cetrulo,
  • Alexandre G. Lellouch,
  • Diala Haykal

摘要

Background

Artificial 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.

Methods

A 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.

Results

From 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.

Conclusion

While 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.