Artificial intelligence in plastic surgery: current developments and future perspectives

Feng Qin , Jianying Gu

Plastic and Aesthetic Research ›› 2023, Vol. 10 ›› Issue (1) : 3

PDF
Plastic and Aesthetic Research ›› 2023, Vol. 10 ›› Issue (1) :3 DOI: 10.20517/2347-9264.2022.72
Review

Artificial intelligence in plastic surgery: current developments and future perspectives

Author information +
History +
PDF

Abstract

Driven by the rapid development of big data, the amount of clinical data, including complex information, is expanding. Traditional data analysis methods cannot meet the need for mining data information, and artificial intelligence (AI) solves this problem. AI is increasingly being incorporated into modern medical practice. Algorithms provided by AI support advanced analysis and provide individualized aid to optimize medical decision-making. In plastic surgery, AI has made many breakthroughs in diagnosis, pre-operative surgical design, treatment decisions, and patient management. Plastic surgeons must recognize AI’s potential development and limitations. This review describes the current application of AI in plastic surgery and discusses the challenges and problems that need to be solved. This study aims to foster the application of this new AI technology in clinical practice.

Keywords

Artificial intelligence / plastic surgery / machine learning / neural networks / natural language processing

Cite this article

Download citation ▾
Feng Qin, Jianying Gu. Artificial intelligence in plastic surgery: current developments and future perspectives. Plastic and Aesthetic Research, 2023, 10(1): 3 DOI:10.20517/2347-9264.2022.72

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Buch VH,Maruthappu M.Artificial intelligence in medicine: current trends and future possibilities.Br J Gen Pract2018;68:143-4 PMCID:PMC5819974

[2]

Saba L,Kuppili V.The present and future of deep learning in radiology.Eur J Radiol2019;114:14-24

[3]

Contreras I.Artificial intelligence for diabetes management and decision support: literature review.J Med Internet Res2018;20:e10775 PMCID:PMC6000484

[4]

Esteva A,Novoa RA.Dermatologist-level classification of skin cancer with deep neural networks.Nature2017;542:115-8

[5]

Chen Z,Yan Z.Artificial intelligence assisted display in thoracic surgery: development and possibilities.J Thorac Dis2021;13:6994-7005 PMCID:PMC8743398

[6]

Saposnik G,Ruff CC.Cognitive biases associated with medical decisions: a systematic review.BMC Med Inform Decis Mak2016;16:138 PMCID:PMC5093937

[7]

Kurmis AP.Artificial intelligence in orthopedic surgery: evolution, current state and future directions.Arthroplasty2022;4:9 PMCID:PMC8889658

[8]

Rajkomar A,Kohane I.Machine learning in medicine.N Engl J Med2019;380:1347-58

[9]

Handelman GS,Chandra RV,Lee MJ.eDoctor: machine learning and the future of medicine.J Intern Med2018;284:603-19

[10]

Kanevsky J,Gaster R,Lin S.Big data and machine learning in plastic surgery: a new frontier in surgical innovation.Plast Reconstr Surg2016;137:890e-7e

[11]

Schwarzer G,Schumacher M.On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology.Statist Med2000;19:541-61

[12]

Lee JG,Cho YW.Deep learning in medical imaging: general overview.Korean J Radiol2017;18:570-84 PMCID:PMC5447633

[13]

Nadkarni PM,Chapman WW.Natural language processing: an introduction.J Am Med Inform Assoc2011;18:544-51 PMCID:PMC3168328

[14]

Topol EJ.High-performance medicine: the convergence of human and artificial intelligence.Nat Med2019;25:44-56

[15]

Patel R,Choudhry HS,Talmor G.Applying machine learning to determine popular patient questions about mentoplasty on social media.Aesthetic Plast Surg2022;46:2273-9

[16]

Levites HA,Levites JB.The use of emotional artificial intelligence in plastic surgery.Plast Reconstr Surg2019;144:499-504

[17]

Boczar D,Oliver JD.Artificial intelligent virtual assistant for plastic surgery patient’s frequently asked questions: a pilot study.Ann Plast Surg2020;84:e16-21

[18]

Chartier C,Lin O,Lee J.BreastGAN: artificial intelligence-enabled breast augmentation simulation.Aesthet Surg J Open Forum2022;4:ojab052 PMCID:PMC8781773

[19]

Chinski H,Tournour D,Caruso D.An artificial intelligence tool for image simulation in rhinoplasty.Facial Plast Surg2022;38:201-6

[20]

Gunes H.Assessing facial beauty through proportion analysis by image processing and supervised learning.Int J Hum Comput Stud2006;64:1184-99

[21]

Crystal DT,Ibrahim AMS,Lin SJ.Photographic and video deepfakes have arrived: how machine learning may influence plastic surgery.Plast Reconstr Surg2020;145:1079-86

[22]

Phillips M,Jaffe W.Assessment of accuracy of an artificial intelligence algorithm to detect melanoma in images of skin lesions.JAMA Netw Open2019;2:e1913436 PMCID:PMC6806667

[23]

Mendoza CS,Okada K,Rogers GF.Personalized assessment of craniosynostosis via statistical shape modeling.Med Image Anal2014;18:635-46

[24]

Bhalodia R,Ayyash AM,Whitaker R.Quantifying the severity of metopic craniosynostosis: a pilot study application of machine learning in craniofacial surgery.J Craniofac Surg2020;31:697-701 PMCID:PMC7202995

[25]

Ferry Q,Webber C.Diagnostically relevant facial gestalt information from ordinary photos.Elife2014;3:e02020 PMCID:PMC4067075

[26]

Kiranantawat K,Taeprasartsit P.The first smartphone application for microsurgery monitoring: silpaRamanitor.Plast Reconstr Surg2014;134:130-9

[27]

Shademan A,Opfermann JD,Krieger A.Supervised autonomous robotic soft tissue surgery.Sci Transl Med2016;8:337ra64

[28]

Li Y,Mei H,Chen Z.CLPNet: cleft lip and palate surgery support with deep learning.Annu Int Conf IEEE Eng Med Biol Soc2019;2019:3666-72

[29]

Turner AE,Davis MJ,Winocour S.Role of simulation and artificial intelligence in plastic surgery training.Plast Reconstr Surg2020;146:390e-1e

[30]

Grenda TR,Dimick JB.Using surgical video to improve technique and skill.Ann Surg2016;264:32-3 PMCID:PMC5671768

[31]

Robnik-šikonja M,Kononenko I.Comprehensible evaluation of prognostic factors and prediction of wound healing.Artif Intell Med2003;29:25-38

[32]

Yeong EK,Chiang HK.Prediction of burn healing time using artificial neural networks and reflectance spectrometer.Burns2005;31:415-20

[33]

Estahbanati HK.Role of artificial neural networks in prediction of survival of burn patients-a new approach.Burns2002;28:579-86

[34]

Kuo PJ,Chien PC.Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer.Oncotarget2018;9:13768-82 PMCID:PMC5862614

[35]

Liao H,Dai W.Age estimation of face images based on CNN and divide-and-rule strategy.Math Model Eng Probl2018;2018:1-8

[36]

Patcas R,Volokitin A,Rothe R.Applying artificial intelligence to assess the impact of orthognathic treatment on facial attractiveness and estimated age.Int J Oral Maxillofac Surg2019;48:77-83

[37]

Iyer TKR,Zhuang Z,Refayee I.Machine learning-based facial beauty prediction and analysis of frontal facial images using facial landmarks and traditional image descriptors.Comput Intell Neurosci2021;2021:4423407 PMCID:PMC8413070

[38]

Khetpal S,Parsaei Y.Perceived age and attractiveness using facial recognition software in rhinoplasty patients: a proof-of-concept study.J Craniofac Surg2022;33:1540-4

[39]

Dorfman R,Saadat S.Making the subjective objective: machine learning and rhinoplasty.Aesthet Surg J2020;40:493-8

[40]

Patcas R,Volokitin A.Facial attractiveness of cleft patients: a direct comparison between artificial-intelligence-based scoring and conventional rater groups.Eur J Orthod2019;41:428-33

[41]

Boonipat T,Lin J,Mardini S.Using artificial intelligence to measure facial expression following facial reanimation surgery.Plast Reconstr Surg2020;146:1147-50

[42]

Dusseldorp JR,van Veen MM,Hadlock TA.In the eye of the beholder: changes in perceived emotion expression after smile reanimation.Plast Reconstr Surg2019;144:457-71

[43]

Chen K,Cheng R.Facial recognition neural networks confirm success of facial feminization surgery.Plast Reconstr Surg2020;145:203-9

[44]

Piwek L,Andrews S.The rise of consumer health wearables: promises and barriers.PLoS Med2016;13:e1001953 PMCID:PMC4737495

[45]

Kayaalp M.Patient privacy in the era of big data.Balkan Med J2018;35:8-17 PMCID:PMC5820452

[46]

Lepri B,Pentland A.Ethical machines: the human-centric use of artificial intelligence.iScience2021;24:102249 PMCID:PMC7973859

[47]

Keskinbora KH.Medical ethics considerations on artificial intelligence.J Clin Neurosci2019;64:277-82

[48]

Maddox TM,Payne PRO.Questions for artificial intelligence in health care.JAMA2019;321:31-2

[49]

Liu J.Artificial intelligence is still far from truly revolutionizing plastic surgery.Plast Reconstr Surg2020;146:390e

PDF

99

Accesses

0

Citation

Detail

Sections
Recommended

/