A Systematic Review of Artificial Intelligence Applications in Plastic Surgery: Looking to the Future. (Record no. 11479)

MARC details
000 -LEADER
fixed length control field 03350nam a22003977a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230316s20222022 xxu||||| |||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 2169-7574
024 ## - OTHER STANDARD IDENTIFIER
Standard number or code 10.1097/GOX.0000000000004608 [doi]
024 ## - OTHER STANDARD IDENTIFIER
Standard number or code PMC9722565 [pmc]
040 ## - CATALOGING SOURCE
Original cataloging agency Ovid MEDLINE(R)
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
PMID 36479133
245 ## - TITLE STATEMENT
Title A Systematic Review of Artificial Intelligence Applications in Plastic Surgery: Looking to the Future.
251 ## - Source
Source Plastic and Reconstructive Surgery - Global Open. 10(12):e4608, 2022 Dec.
252 ## - Abbreviated Source
Abbreviated source Plast. reconstr. surg., Glob. open. 10(12):e4608, 2022 Dec.
253 ## - Journal Name
Journal name Plastic and reconstructive surgery. Global open
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Year 2022
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Manufacturer FY2023
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Publication date 2022 Dec
265 ## - SOURCE FOR ACQUISITION/SUBSCRIPTION ADDRESS [OBSOLETE]
Publication status epublish
265 ## - SOURCE FOR ACQUISITION/SUBSCRIPTION ADDRESS [OBSOLETE]
Medline status PubMed-not-MEDLINE
520 ## - SUMMARY, ETC.
Abstract 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.
520 ## - SUMMARY, ETC.
Abstract 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.
520 ## - SUMMARY, ETC.
Abstract 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.
520 ## - SUMMARY, ETC.
Abstract 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.
546 ## - LANGUAGE NOTE
Language note English
651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME
Institution MedStar Washington Hospital Center
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Department MedStar Georgetown University Hospital/MedStar Washington Hospital Center
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Department Plastic Surgery Residency
656 ## - INDEX TERM--OCCUPATION
Department Surgery/Plastic Surgery
657 ## - INDEX TERM--FUNCTION
Medline publication type Journal Article
700 ## - ADDED ENTRY--PERSONAL NAME
Local Authors Abadeer, Andrew
Institution Code MGUH
Program Plastic Surgery Residency
Degree MD
Resident year Resident PGY 5
700 ## - ADDED ENTRY--PERSONAL NAME
Local Authors Fan, Kenneth L
Institution Code MWHC
790 ## - Authors
All authors Spoer DL
-- Kiene JM
-- Dekker PK
-- Huffman SS
-- Kim KG
-- Abadeer AI
-- Fan KL
856 ## - ELECTRONIC LOCATION AND ACCESS
DOI <a href="https://dx.doi.org/10.1097/GOX.0000000000004608">https://dx.doi.org/10.1097/GOX.0000000000004608</a>
Public note https://dx.doi.org/10.1097/GOX.0000000000004608
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Journal Article
Item type description Journal Article
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              03/16/2023   36479133 36479133 03/16/2023 03/16/2023 Journal Article

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