TY  - BOOK
AU  - Abadeer, Andrew 
AU  - Fan, Kenneth L
TI  - A Systematic Review of Artificial Intelligence Applications in Plastic Surgery: Looking to the Future
SN  - 2169-7574
PY  - 2022///
KW  - MedStar Washington Hospital Center
KW  - MedStar Georgetown University Hospital/MedStar Washington Hospital Center
KW  - Plastic Surgery Residency
KW  - Surgery/Plastic Surgery
KW  - Journal Article
N2  - 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; 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. Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The American Society of Plastic Surgeons; 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
UR  - https://dx.doi.org/10.1097/GOX.0000000000004608
ER  -