REFERENCES

1. Reyes JA, Puerta Romero M, Cobo R, Heredia N, Solís Ruiz LA, Corredor Zuluaga DA. Artificial intelligence in facial plastic and reconstructive surgery: a systematic review. Facial Plast Surg 2024;40:615-22.

2. Cogno N, Axenie C, Bauer R, Vavourakis V. Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation. Cancer Biol Ther 2024;25:2344600.

3. Jiang L, Zhou Y, Miao W, et al. Artificial intelligence-assisted quantitative CT parameters in predicting the degree of risk of solitary pulmonary nodules. Ann Med 2024;56:2405075.

4. Park KW, Diop M, Willens SH, Pepper JP. Artificial intelligence in facial plastics and reconstructive surgery. Otolaryngol Clin North Am 2024;57:843-52.

5. Jarvis T, Thornburg D, Rebecca AM, Teven CM. Artificial intelligence in plastic surgery: current applications, future directions, and ethical implications. Plast Reconstr Surg Glob Open 2020;8:e3200.

6. Wolfs JAGN, Schols RM, van Mulken TJM. Robotic microvascular and free flap surgery: overview of current robotic applications and introduction of a dedicated robot for microsurgery. In: Nikkhah D, Rawlins J, Pafitanis G, editors. Core techniques in flap reconstructive microsurgery. Cham: Springer International Publishing; 2023. pp. 77-86.

7. Guni A, Varma P, Zhang J, Fehervari M, Ashrafian H. Artificial intelligence in surgery: the future is now. Eur Surg Res 2024;65:22-39.

8. Liang X, Yang X, Yin S, et al. Artificial intelligence in plastic surgery: applications and challenges. Aesthetic Plast Surg 2021;45:784-90.

9. Cevik J, Seth I, Hunter-Smith DJ, Rozen WM. A history of innovation: tracing the evolution of imaging modalities for the preoperative planning of microsurgical breast reconstruction. J Clin Med 2023;12:5246.

10. Schmale IL, Vandelaar LJ, Luong AU, Citardi MJ, Yao WC. Image-guided surgery and intraoperative imaging in rhinology: clinical update and current state of the art. Ear Nose Throat J 2021;100:NP475-86.

11. Luz M, Strauss G, Manzey D. Impact of image-guided surgery on surgeons’ performance: a literature review. IJHFE 2016;4:229-63.

12. Kim Y, Kim H, Kim YO. Virtual reality and augmented reality in plastic surgery: a review. Arch Plast Surg 2017;44:179-87.

13. Lin HH, Lo LJ. Three-dimensional computer-assisted surgical simulation and intraoperative navigation in orthognathic surgery: a literature review. J Formos Med Assoc 2015;114:300-7.

14. Glas HH, Kraeima J, van Ooijen PMA, Spijkervet FKL, Yu L, Witjes MJH. Augmented reality visualization for image-guided surgery: a validation study using a three-dimensional printed phantom. J Oral Maxillofac Surg 2021;79:1943.e1-10.

15. Murphy DC, Saleh DB. Artificial intelligence in plastic surgery: What is it? Where are we now? What is on the horizon? Ann R Coll Surg Engl 2020;102:577-80.

16. Park BJ, Hunt SJ, Martin C 3rd, Nadolski GJ, Wood BJ, Gade TP. Augmented and mixed reality: technologies for enhancing the future of IR. J Vasc Interv Radiol 2020;31:1074-82.

17. Palumbo A. Microsoft HoloLens 2 in medical and healthcare context: state of the art and future prospects. Sensors 2022;22:7709.

18. Pratt P, Ives M, Lawton G, et al. Through the HoloLens™ looking glass: augmented reality for extremity reconstruction surgery using 3D vascular models with perforating vessels. Eur Radiol Exp 2018;2:2.

19. Al Janabi HF, Aydin A, Palaneer S, et al. Effectiveness of the HoloLens mixed-reality headset in minimally invasive surgery: a simulation-based feasibility study. Surg Endosc 2020;34:1143-9.

20. Fitoussi A, Tacher V, Pigneur F, et al. Augmented reality-assisted deep inferior epigastric artery perforator flap harvesting. J Plast Reconstr Aesthet Surg 2021;74:1931-71.

21. Microsoft Stories Asia. AI in the operating theater: technology transforms cosmetic surgery in Korea. 2018. Available from: https://news.microsoft.com/apac/features/ai-in-the-operating-theater-technology-transforms-cosmetic-surgery-in-korea/. [Last accessed on 2 Nov 2024].

22. Shademan A, Decker RS, Opfermann JD, Leonard S, Krieger A, Kim PC. Supervised autonomous robotic soft tissue surgery. Sci Transl Med 2016;8:337ra64.

23. Lindenblatt N, Grünherz L, Wang A, et al. Early experience using a new robotic microsurgical system for lymphatic surgery. Plast Reconstr Surg Glob Open 2022;10:e4013.

24. Dunn J, Yeo E, Moghaddampour P, Chau B, Humbert S. Virtual and augmented reality in the treatment of phantom limb pain: a literature review. NeuroRehabilitation 2017;40:595-601.

25. Javed H, Olanrewaju OA, Ansah Owusu F, et al. Challenges and solutions in postoperative complications: a narrative review in general surgery. Cureus 2023;15:e50942.

26. Hashimoto DA, Rosman G, Rus D, Meireles OR. Artificial intelligence in surgery: promises and perils. Ann Surg 2018;268:70-6.

27. Wen R, Zheng K, Zhang Q, et al. Machine learning-based random forest predicts anastomotic leakage after anterior resection for rectal cancer. J Gastrointest Oncol 2021;12:921-32.

28. Willan J, King AJ, Jeffery K, Bienz N. Challenges for NHS hospitals during covid-19 epidemic. BMJ 2020;368:m1117.

29. Bielsa VF. Virtual reality simulation in plastic surgery training. literature review. J Plast Reconstr Aesthet Surg 2021;74:2372-8.

30. Lareyre F, Adam C, Carrier M, Chakfé N, Raffort J. Artificial intelligence for education of vascular surgeons. Eur J Vasc Endovasc Surg 2020;59:870-1.

31. Dave M, Patel N. Artificial intelligence in healthcare and education. Br Dent J 2023;234:761-4.

32. Moglia A, Georgiou K, Georgiou E, Satava RM, Cuschieri A. A systematic review on artificial intelligence in robot-assisted surgery. Int J Surg 2021;95:106151.

33. Deo RC. Machine learning in medicine. Circulation 2015;132:1920-30.

34. Sutton RS, Barto AG. Reinforcement learning, second edition. An introduction. MIT Press, 2018. Available from: https://mitpress.mit.edu/9780262039246/reinforcement-learning/. [Last accessed on 2 Nov 2024].

35. Nogueira R, Eguchi M, Kasmirski J, et al. Machine learning, deep learning, artificial intelligence and aesthetic plastic surgery: a qualitative systematic review. Aesthetic Plast Surg 2024.

36. Wang PS, Walker A, Tsuang M, Orav EJ, Levin R, Avorn J. Strategies for improving comorbidity measures based on Medicare and Medicaid claims data. J Clin Epidemiol 2000;53:571-8.

37. Mofidi R, Duff MD, Madhavan KK, Garden OJ, Parks RW. Identification of severe acute pancreatitis using an artificial neural network. Surgery 2007;141:59-66.

38. Chen M, Decary M. Artificial intelligence in healthcare: an essential guide for health leaders. Healthc Manage Forum 2020;33:10-8.

39. Chan HP, Samala RK, Hadjiiski LM, Zhou C. Deep learning in medical image analysis. Adv Exp Med Biol 2020;1213:3-21.

40. Ghods K, Azizi A, Jafari A, Ghods K. Application of artificial intelligence in clinical dentistry, a comprehensive review of literature. J Dent 2023;24:356-71.

41. Benke K, Benke G. Artificial intelligence and big data in public health. Int J Environ Res Public Health 2018;15:2796.

42. Wang SY, Pershing S, Lee AY; AAO Taskforce on AI and AAO Medical Information Technology Committee. Big data requirements for artificial intelligence. Curr Opin Ophthalmol 2020;31:318-23.

43. Kayaalp M. Patient privacy in the era of big data. Balkan Med J 2018;35:8-17.

44. Zulhuda S, Abdul Ghani Azmi IM, Hakiem N. Big data, cloud and bring your own device: how the data protection law addresses the impact of “datafication”. Adv Sci Lett 2015;21:3346-50.

45. Information Commissioner’s Office. Big data, artificial intelligence, machine learning and data protection. Available from: https://ico.org.uk/media/for-organisations/documents/2013559/big-data-ai-ml-and-data-protection.pdf. [Last accessed on 2 Nov 2024].

46. Pesapane F, Codari M, Sardanelli F. Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp 2018;2:35.

47. Brinker TJ, Hekler A, Enk AH, et al; Collaborators. Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. Eur J Cancer 2019;113:47-54.

48. Ozmen BB, Schwarz GS. Future of artificial intelligence in plastic surgery: toward the development of specialty-specific large language models. J Plast Reconstr Aesthet Surg 2024;93:70-1.

49. Mir MA. Artificial intelligence revolutionizing plastic surgery scientific publications. Cureus 2023;15:e40770.

50. Qin F, Gu J. Artificial intelligence in plastic surgery: current developments and future perspectives. Plast Aesthet Res 2023;10:3.

51. O’Sullivan S, Nevejans N, Allen C, et al. Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery. Int J Med Robot 2019;15:e1968.

52. Kim YJ, Kelley BP, Nasser JS, Chung KC. Implementing precision medicine and artificial intelligence in plastic surgery: concepts and future prospects. Plast Reconstr Surg Glob Open 2019;7:e2113.

53. Digital surgery deploys first surgical artificial intelligence system for the operating room. 2018. Available from: https://www.businesswire.com/news/home/20180716005146/en/Digital-Surgery-Deploys-First-Surgical-Artificial-Intelligence-System-for-the-Operating-Room. [Last accessed on 2 Nov 2024].

54. Gonçalves-Bradley DC, Lannin NA, Clemson L, Cameron ID, Shepperd S. Discharge planning from hospital. Cochrane Database Syst Rev 2022;2:CD000313.