The Role of Artificial Intelligence in Plastic Surgery: Review, Applications, and Future Prospects to Revolutionize Patients Outcomes, Safety and Satisfaction

Main Article Content

Ahmad Fawzy

Abstract

The integration of artificial intelligence (AI) in plastic surgery holds immense potential for transforming the field, improving outcomes, and enhancing patient satisfaction. This article examines the application of AI in pre-operative planning, intra-operative decision making, and post-operative monitoring. AI tools leverage patient images to provide valuable insights into surgical outcomes, aiding in visualization and communication. Real-time guidance during surgery is facilitated by AI's analysis of intra-operative images, ensuring accurate execution and enhancing safety. In post-operative monitoring, AI analyzes patient data to predict outcomes, detect complications, and optimize wound healing assessment. Despite challenges, the future of AI in plastic surgery looks promising, with advancements in augmented reality, mobile applications, computer vision, and robotically assisted treatments driving progress and strengthening patient-physician relationships.

Article Details

How to Cite
Fawzy, A. . (2023). The Role of Artificial Intelligence in Plastic Surgery: Review, Applications, and Future Prospects to Revolutionize Patients Outcomes, Safety and Satisfaction. International Journal of Medical Science and Clinical Research Studies, 3(11), 2734–2739. https://doi.org/10.47191/ijmscrs/v3-i11-36
Section
Articles

References

I. Turing AM. Computing Machinery and Intelligence [Internet]. Department of Computer Science and Electrical Engineering - UMBC. [cited 2023Apr3]. Available from:

https://www.csee.umbc.edu/courses/471/papers/turing.pdf

II. History Computer. Logic Theorist explained - everything you need to know [Internet]. History. 2022 [cited 2023Apr3]. Available from: https://history-computer.com/logic-theorist/

III. Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine. Gastrointest Endosc. 2020 Oct;92(4):807-812.DOI: 10.1016/j.gie.2020.06.040.

IV. Rokhshad R, Keyhan SO, Yousefi P. Artificial intelligence applications and ethical challenges in oral and maxillo-facial cosmetic surgery: a narrative review. Maxillofac Plast Reconstr Surg. 2023 Mar 13;45(1):14. doi: 10.1186/s40902-023-00382-w.

V. Hosny A, Parmar C, Quackenbush J, Schwartz LH, Aerts HJWL. Artificial intelligence in radiology. Nat Rev Cancer. 2018 Aug;18(8):500-510. doi: 10.1038/s41568-018-0016-5.

VI. Eldaly AS, Avila FR, Torres-Guzman RA, Maita K, Garcia JP, Palmieri Serrano L, Forte AJ. Simulation and Artificial Intelligence in Rhinoplasty: A Systematic Review. Aesthetic Plast Surg. 2022 Oct;46(5):2368-2377. doi: 10.1007/s00266-022-02883-x.

VII. Knoedler L, Odenthal J, Prantl L, Oezdemir B, Kehrer A, Kauke-Navarro M, Matar DY, Obed D, Panayi AC, Broer PN, Chartier C, Knoedler S. Artificial intelligence-enabled simulation of gluteal augmentation: A helpful tool in preoperative outcome simulation? J Plast Reconstr Aesthet Surg. 2023 Feb 9;80:94-101. doi: 10.1016/j.bjps.2023.01.039.

VIII. Parsa S, Basagaoglu B, Mackley K, Aitson P, Kenkel J, Amirlak B. Current and Future Photography Techniques in Aesthetic Surgery. Aesthet Surg J Open Forum. 2021 Nov 29;4:ojab050. doi: 10.1093/asjof/ojab050.

IX. Song H, Lee S, Kim J, Sohn K. Three-dimensional sensor-based face recognition. Appl Opt. 2005 Feb 10;44(5):677-87. doi: 10.1364/ao.44.000677.

X. Alam IS, Steinberg I, Vermesh O, van den Berg NS, Rosenthal EL, van Dam GM, et al. Emerging intraoperative imaging modalities to improve surgical precision. Mol Imaging Biol. 2018 Oct;20(5):705-715. doi: 10.1007/s11307-018-1227-6.

XI. Morris MX, Rajesh A, Asaad M, Hassan A, Saadoun R, Butler CE. Deep learning applications in surgery: Current uses and future directions. Am Surg. 2023 Jan;89(1):36-42.doi: 10.1177/00031348221101490.

XII. Shuhaiber JH. Augmented reality in surgery. Arch Surg. 2004 Feb;139(2):170-4.doi: 10.1001/archsurg.139.2.170.

XIII. Kim Y, Kim H, Kim YO. Virtual reality and augmented reality in plastic surgery: A review. Arch Plast Surg. 2017 May;44(3):179-187. doi: 10.5999/aps.2017.44.3.179.

XIV. Zhou XY, Guo Y, Shen M, Yang GZ. Application of artificial intelligence in surgery. Front Med. 2020 Aug;14(4):417-430. doi: 10.1007/s11684-020-0770-0.

XV. Kim BS, Zhang Z, Sun M, Han W, Chen X, Yan Y, et al. Feasibility of a robot-assisted surgical navigation system for mandibular distraction osteogenesis in hemifacial microsomia: A model experiment. J Craniofac Surg. 2023 Mar-Apr 01;34(2):525-531.

a. doi: 10.1097/SCS.0000000000009028.

XVI. Andersen NK, Trøjgaard P, Herschend NO, Størling ZM. Automated assessment of peristomal skin discoloration and leakage area using artificial intelligence. Front Artif Intell. 2020 Sep 10;3:72. doi: 10.3389/frai.2020.00072.

XVII. Maffulli N, Rodriguez HC, Stone IW, Nam A, Song A, Gupta M, et al. Artificial intelligence and machine learning in orthopedic surgery: a systematic review protocol. J Orthop Surg Res. 2020 Oct 19;15(1):478. doi: 10.1186/s13018-020-02002-z.

XVIII. Xue B, Li D, Lu C, King CR, Wildes T, Avidan MS, et al. Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications. JAMA Netw Open. 2021 Mar 1;4(3):e212240.doi: 10.1001/jamanetworkopen.2021.2240.

XIX. Sha S, Du W, Parkinson A, Glasgow N. Relative importance of clinical and sociodemographic factors in association with post-operative in-hospital deaths in colorectal cancer patients in New South Wales: An artificial neural network approach. J Eval Clin Pract. 2020 Oct;26(5):1389-1398. doi: 10.1111/jep.13318.

XX. Ohura N, Mitsuno R, Sakisaka M, Terabe Y, Morishige Y, Uchiyama A, et al. Convolutional neural networks for wound detection: the role of artificial intelligence in wound care. J Wound Care. 2019 Oct 1;28(Sup10):S13-S24.

doi: 10.12968/jowc.2019.28.Sup10.S13.

PMID: 31600101.

XXI. Ngiam KY, Khor IW. Big data and machine learning algorithms for health-care delivery. Lancet Oncol. 2019 May;20(5):e262-e273. doi: 10.1016/S1470-2045(19)30149-4. Erratum in: Lancet Oncol. 2019 Jun;20(6):293.

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