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CC BY 4.0 · Revista Brasileira de Cirurgia Plástica (RBCP) – Brazilian Journal of Plastic Surgery 2025; 40: s00451806918
DOI: 10.1055/s-0045-1806918
Artigo de Revisão

Limitations and Challenges in the Incorporation of Artificial Intelligence in Plastic Surgery: A Systematic Review

Article in several languages: português | English
Carolina Guimarães Herzog 
1   Departamento de Medicina, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brasil
,
Georgia Marques Jardim 
1   Departamento de Medicina, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brasil
,
Alexandre Perin Decol 
1   Departamento de Medicina, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brasil
,
Vinicius Urbano Palma 
1   Departamento de Medicina, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brasil
,
Gabriel de Paula Alves 
1   Departamento de Medicina, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brasil
,
Rafaela Dall Ara Negri 
1   Departamento de Medicina, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brasil
,
Andrielle Miozzo Soares 
1   Departamento de Medicina, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brasil
,
Denis Souto Valente 
2   Departamento de Clínica Cirúrgica, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS Brasil
› Author Affiliations Financial Support The authors declare that they did not receive financial support from agencies in the public, private, or non-profit sectors to conduct the present study.

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Abstract

The present systematic review provides a comprehensive analysis of the current role of artificial intelligence (AI) in plastic surgery, focusing on its applications, outcomes, challenges, and limitations. Out of an initial pool of 213 articles, 74 studies were included after a rigorous selection process based on relevance and methodological quality. Among the AI technologies evaluated, augmented reality (AR) stands out as an emerging tool with significant potential to enhance visualization and planning in esthetic and reconstructive procedures. The use of AR facilitates advancements in volume projection, shape, and symmetry, helping to reduce patient anxiety and better align surgical expectations by offering more precise preoperative visualization. Despite the identified benefits, the implementation of these technologies faces considerable challenges. The lack of specific regulations and the need for adequate technical training for healthcare professionals are significant barriers to the full integration of AI into the clinical practice. Additionally, the heterogeneity of studies and the lack of standardized outcomes make it difficult to generalize the observed benefits. The review concludes that, although the advances are promising, there is a critical need for further studies that address existing gaps and for robust regulations to ensure the safe and effective adoption of AI in contemporary plastic surgery.

Keywords

artificial intelligence - diagnosis - computer-assisted - machine learning - plastic surgery procedures - surgery - plastic

Authors' Contributions

CGH: data analysis and/or interpretation, final manuscript approval, conceptualization, study conception and design, project management, investigation, methodology, writing – original draft. preparation, writing – review & editing, and supervision; GMJ: data analysis and/or interpretation, final manuscript approval, study conception and design, project management, methodology, writing – original draft, and writing – review & editing; APD: data analysis and/or interpretation data collection, conceptualization, methodology, writing – original draft, writing – review & editing, and supervision; VUP: data analysis and/or interpretation, statistical analysis, data collection, methodology, and writing – review & editing; GPA: data analysis and/or interpretation statistical analysis, final manuscript approval, data collection, and writing – review & editing; RDAN: data analysis and/or interpretation statistical analysis, data collection, and methodology; AMS: data analysis and/or interpretation study conception and design, and methodology; and DSV: data analysis and/or interpretation final manuscript approval, conceptualization, study conception and design, project management, methodology, writing – original draft, writing – review & editing, and supervision.




Publication History

Received: 01 September 2024

Accepted: 16 November 2024

Article published online:
30 April 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit (https://creativecommons.org/licenses/by/4.0/)

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Bibliographical Record
Carolina Guimarães Herzog, Georgia Marques Jardim, Alexandre Perin Decol, Vinicius Urbano Palma, Gabriel de Paula Alves, Rafaela Dall Ara Negri, Andrielle Miozzo Soares, Denis Souto Valente. Limitações e desafios na incorporação da inteligência artificial em cirurgia plástica: Uma revisão sistemática. Revista Brasileira de Cirurgia Plástica (RBCP) – Brazilian Journal of Plastic Surgery 2025; 40: s00451806918.
DOI: 10.1055/s-0045-1806918
 

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