Page 28 - Read Online

Brenac et al. Art Int Surg 2024;4:296-315 Artificial
DOI: 10.20517/ais.2024.49
Intelligence Surgery

Review Open Access

AI in plastic surgery: customizing care for each
patient

1
1
1
1
Camille Brenac 1,2 , Alexander Z. Fazilat , Mahsa Fallah , Danae Kawamoto-Duran , Parker S. Sunwoo ,
1
1,3
Michael T. Longaker , Derrick C. Wan , Jason L. Guo 1,3
1
Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery,
Stanford University School of Medicine, Stanford, CA 94305, USA.
2
Department of Plastic, Reconstructive and Aesthetic Surgery, hospices civils de Lyon, Croix-Rousse Hospital, Lyon 69004,
France.
3
Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305, USA.
Correspondence to: Prof. Derrick C. Wan, Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and
Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, 257 Campus Drive, Stanford, CA
94305, USA. E-mail: dwan@stanford.edu
How to cite this article: Brenac C, Fazilat AZ, Fallah M, Kawamoto-Duran D, Sunwoo PS, Longaker MT, Wan DC, Guo JL. AI in
plastic surgery: customizing care for each patient. Art Int Surg 2024;4:296-315. https://dx.doi.org/10.20517/ais.2024.49
Received: 11 Jul 2024 First Decision: 7 Aug 2024 Revised: 3 Sep 2024 Accepted: 25 Sep 2024 Published: 15 Oct 2024

Academic Editor: Andrew A. Gumbs Copy Editor: Pei-Yun Wang Production Editor: Pei-Yun Wang

Abstract
Artificial intelligence (AI) and machine learning (ML) involve the usage of complex algorithms to identify patterns,
predict future outcomes, generate new data, and perform other tasks that typically require human intelligence. AI
tools have been progressively adopted by multiple disciplines of surgery, enabling increasingly patient-specific
care, as well as more precise surgical modeling and assessment. For instance, AI tools such as ChatGPT have been
applied to enhance both patient educational materials and patient-surgeon communication. Additionally, AI tools
have helped support pre- and postoperative assessment in a diverse set of procedures, including breast
reconstructions, facial surgeries, hand surgeries, wound healing operations, and burn surgeries. Further, ML-
supported 3D modeling has now been utilized for patient-specific surgical planning and may also be combined with
3D printing technologies to generate patient-customized, implantable constructs. Ultimately, the advent of AI and
its intersection with surgical practice have demonstrated immense potential to transform patient care by making
multiple facets of the surgical process more efficient, precise, and patient-specific.

Keywords: Plastic surgery, machine learning, artificial intelligence, algorithms

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
indicate if changes were made.

www.oaepublish.com/ais