From scalpel to software: the potential role of AI in plastic surgery training - a scoping review

Abstract

Aim: The evolving capabilities of artificial intelligence (AI) are revolutionizing medicine, and AI integration into surgical training has produced novel tools that are altering the educational landscape. Therefore, the aim of this review is to demonstrate current and future applications of AI in plastic surgery training.

Methods: A detailed search was performed using PubMed and other search engines for applications of AI within surgical education.

Results: Of papers that met inclusion criteria, eight addressed AI in plastic surgery education, with others addressing general surgery (n = 4), neurosurgery (n = 3), endodontics (n = 1), obstetrics/gynecology (n = 1), orthopedic surgery (n = 1), urology (n = 1), and craniofacial surgery (n = 1). Three key areas of research emerged: supplemental/independent learning, operative skills practice, and resident feedback.

Conclusions: Novel applications of various AI algorithms within these areas were explored. The limited integration of AI into plastic surgery education compared with other surgical specialties and the limitations inherent to AI were also highlighted. Though limited research has specifically examined the applications of AI in plastic surgery education, its potential as a versatile educational tool within the field is evident. Novel AI algorithms are already enhancing study tools, surgical skill acquisition, and feedback. Further study is imperative to investigate outlets that leverage AI for the advancement of plastic surgery education.

Keywords

Artificial intelligence / machine learning / natural language processing / surgical training / plastic surgery education

References

[1] Poole D,Goebel R. Computational intelligence: a logical approach. Oxford University Press; 1998. Available from: https://www.researchgate.net/publication/220689680_Computational_Intelligence_A_Logical_Approach. [Last accessed on 24 Jun 2025]

[2] OpenAI. ChatGPT (Version 4) Large language model. OpenAI. 2024. Available from: https://chatgpt.com/. [Last accessed on 24 Jun 2025]

[3] Nagi F,Alzubaidi M.Applications of artificial intelligence (AI) in medical education: a scoping review.Stud Health Technol Inform2023;305:648-51

[4] Luce EA.The future of plastic surgery resident education.Plast Reconstr Surg2016;137:1063-70

[5] Farid Y,Ortiz S.Artificial intelligence in plastic surgery: insights from plastic surgeons, education integration, ChatGPT’s survey predictions, and the path forward.Plast Reconstr Surg Glob Open2024;12:e5515 PMCID:PMC10781127

[6] Kapila AK.Time to evolve plastic surgery education? Integrating robotic techniques and artificial intelligence into training curricula.Plast Reconstr Surg Glob Open2024;12:e5778 PMCID:PMC11062664

[7] St John A, Cooper L, Kavic SM. The role of artificial intelligence in surgery: what do general surgery residents think?.Am Surg2024;90:541-9

[8] Tricco AC,Zarin W.PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation.Ann Intern Med2018;169:467-73

[9] DiDonna N,Khan K.Unveiling the potential of AI in plastic surgery education: a comparative study of leading AI platforms’ performance on in-training examinations.Plast Reconstr Surg Glob Open2024;12:e5929 PMCID:PMC11191997

[10] Gupta R,Park JB.Performance of ChatGPT on the plastic surgery inservice training examination.Aesthet Surg J2023;43:NP1078-82

[11] Hubany SS,Hashemi K.ChatGPT-4 surpasses residents: a study of artificial intelligence competency in plastic surgery in-service examinations and its advancements from ChatGPT-3.5.Plast Reconstr Surg Glob Open2024;12:e6136 PMCID:PMC11377087

[12] Humar P,Bengur FB.ChatGPT is equivalent to first-year plastic surgery residents: evaluation of ChatGPT on the plastic surgery in-service examination.Aesthet Surg J2023;43:NP1085-9

[13] Koljonen V.What could we make of AI in plastic surgery education.J Plast Reconstr Aesthet Surg2023;81:94-6

[14] Saadya A.Revolutionizing plastic surgery education: leveraging artificial intelligence for an innovative podcast learning platform.Plast Reconstr Surg2024;154:847e-8e

[15] Shah P,Patel PA.Assessing the plastic surgery knowledge of three natural language processor artificial intelligence programs.J Plast Reconstr Aesthet Surg2024;88:193-5

[16] Zhang A,Gupta R.The new frontier: utilizing ChatGPT to expand craniofacial research.Arch Craniofac Surg2024;25:116-22 PMCID:PMC11231409

[17] Hui Z,Jiao H.Application of ChatGPT-assisted problem-based learning teaching method in clinical medical education.BMC Med Educ2025;25:50 PMCID:PMC11724493

[18] Li TP,Sahoo A.Socratic artificial intelligence learning (SAIL): the role of a virtual voice assistant in learning orthopedic knowledge.J Surg Educ2024;81:1655-66

[19] Fazlollahi AM,Alsayegh A.Effect of artificial intelligence tutoring vs expert instruction on learning simulated surgical skills among medical students: a randomized clinical trial.JAMA Netw Open2022;5:e2149008 PMCID:PMC8864513

[20] Fukuta A,Maniwa J.Artificial intelligence facilitates the potential of simulator training: an innovative laparoscopic surgical skill validation system using artificial intelligence technology.Int J Comput Assist Radiol Surg2025;20:597-603 PMCID:PMC11929722

[21] Sayadi LR,Zhangli Q,Vyas RM.Harnessing the power of artificial intelligence to teach cleft lip surgery.Plast Reconstr Surg Glob Open2022;10:e4451 PMCID:PMC9325328

[22] Siyar S,Rashidi S.Machine learning distinguishes neurosurgical skill levels in a virtual reality tumor resection task.Med Biol Eng Comput2020;58:1357-67

[23] Vannaprathip N,Schultheis H.Intelligent tutoring for surgical decision making: a planning-based approach.Int J Artif Intell Educ2022;32:350-81

[24] Yilmaz R,Mirchi N.Continuous monitoring of surgical bimanual expertise using deep neural networks in virtual reality simulation.NPJ Digit Med2022;5:54 PMCID:PMC9042967

[25] Lei T,Feng J.Enhancing trainee performance in obstetric ultrasound through an artificial intelligence system: randomized controlled trial.Ultrasound Obstet Gynecol2024;64:453-62

[26] Ötleş E,Solano QP.Using natural language processing to automatically assess feedback quality: findings from 3 surgical residencies.Acad Med2021;96:1457-60

[27] Solano QP,Chopra Z.Natural language processing and assessment of resident feedback quality.J Surg Educ2021;78:e72-7

[28] Stahl CC,Rosser AA.Natural language processing and entrustable professional activity text feedback in surgery: a machine learning model of resident autonomy.Am J Surg2021;221:369-75 PMCID:PMC7969407

[29] Tesfaye EA,Butler CE.Podcasts in plastic surgery: where do we currently stand?.Plast Reconstr Surg2022;149:371e-3e

[30] Schöbel T,Melcher P.Podcasts as a teaching tool in orthopaedic surgery: is it beneficial or more an exemption card from attending lectures?.Orthopade2021;50:455-63 PMCID:PMC8189972

[31] Vanstrum EB,Wu FM.The role of educational podcast use among otolaryngology residents.Ann Otol Rhinol Laryngol2022;131:1353-7

[32] Little A,Gronowski T,Kalnow A.Podcasting in medicine: a review of the current content by specialty.Cureus2020;12:e6726 PMCID:PMC7032601

[33] Clarke C,Mughal M.Podcasts in plastic surgery, why we should start listening.J Plast Reconstr Aesthet Surg2021;74:1633-701

[34] Fang Z,He X.Artificial intelligence-based pathologic myopia identification system in the ophthalmology residency training program.Front Cell Dev Biol2022;10:1053079 PMCID:PMC9669055

[35] Lebhar MS,Goza S.Dr. ChatGPT: utilizing artificial intelligence in surgical education.Cleft Palate Craniofac J2024;61:2067-73

[36] Cabitza F,Gensini GF.Unintended consequences of machine learning in medicine.JAMA2017;318:517-8

[37] Kohli M.Ethics, artificial intelligence, and radiology.J Am Coll Radiol2018;15:1317-9

[38] Lohre R,Pollock JW.Effectiveness of immersive virtual reality on orthopedic surgical skills and knowledge acquisition among senior surgical residents: a randomized clinical trial.JAMA Netw Open2020;3:e2031217 PMCID:PMC7770558

[39] Page MJ.The PRISMA 2020 statement: an updated guideline for reporting systematic reviews.BMJ2021;372:n71