Abstract and Introduction
Background: Artificial intelligence (AI) is presently employed in several medical specialties, particularly those that rely on large quantities of standardized data. The integration of AI in surgical subspecialties is under preclinical investigation but is yet to be widely implemented. Plastic surgeons collect standardized data in various settings and could benefit from AI. This systematic review investigates the current clinical applications of AI in plastic and reconstructive surgery.
Methods: A comprehensive literature search of the Medline, EMBASE, Cochrane, and PubMed databases was conducted for AI studies with multiple search terms. Articles that progressed beyond the title and abstract screening were then subcategorized based on the plastic surgery subspecialty and AI application.
Results: The systematic search yielded a total of 1820 articles. Forty-four studies met inclusion criteria warranting further analysis. Subcategorization of articles by plastic surgery subspecialties revealed that most studies fell into aesthetic and breast surgery (27%), craniofacial surgery (23%), or microsurgery (14%). Analysis of the research study phase of included articles indicated that the current research is primarily in phase 0 (discovery and invention; 43.2%), phase 1 (technical performance and safety; 27.3%), or phase 2 (efficacy, quality improvement, and algorithm performance in a medical setting; 27.3%). Only one study demonstrated translation to clinical practice.
Conclusions: The potential of AI to optimize clinical efficiency is being investigated in every subfield of plastic surgery, but much of the research to date remains in the preclinical status. Future implementation of AI into everyday clinical practice will require collaborative efforts.
Artificial intelligence (AI) is unified by the idea of a system that displays intelligent behavior. AI's robust automated computing power can reduce diagnostic errors, conserve resources, and increase efficiency.[1–3] The most successful clinical applications of AI are seen in medical specialties that inherently collect standardized data, such as radiology, pathology, ophthalmology, and dermatology. Conversely, the decreased emphasis on standardized data collection in surgery may be limiting an associated development of clinical AI. Plastic surgery is uniquely reliant on visual diagnosis, prediction, and assessment of aesthetic outcomes. Such AI tasks are achievable and could enhance efficiency and accuracy in plastic surgery. However, the standardization of data and integration of AI in plastic surgery is not well characterized.
In this systematic review, we aim to investigate the current applications of AI in plastic surgery within eight subspecialties: aesthetic and breast surgery, general plastic and reconstructive surgery, craniofacial surgery, burn surgery, microsurgery, oral and maxillofacial surgery, wound care, and hand surgery. We further distinguish the AI implemented in each study by subfield (Table 1) and study phase to characterize current applications and future directions for integrating AI into clinical practice.[2,4,5–18]
Plast Reconstr Surg Glob Open. 2022;10(12):e4608 © 2022 Lippincott Williams & Wilkins