REFERENCES

1. Buch VH, Ahmed I, Maruthappu M. Artificial intelligence in medicine: current trends and future possibilities. Br J Gen Pract 2018;68:143-4.

2. Saba L, Biswas M, Kuppili V, et al. The present and future of deep learning in radiology. Eur J Radiol 2019;114:14-24.

3. Contreras I, Vehi J. Artificial intelligence for diabetes management and decision support: literature review. J Med Internet Res 2018;20:e10775.

4. Esteva A, Kuprel B, Novoa RA, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017;542:115-8.

5. Chen Z, Zhang Y, Yan Z, et al. Artificial intelligence assisted display in thoracic surgery: development and possibilities. J Thorac Dis 2021;13:6994-7005.

6. Saposnik G, Redelmeier D, Ruff CC, Tobler PN. Cognitive biases associated with medical decisions: a systematic review. BMC Med Inform Decis Mak 2016;16:138.

7. Kurmis AP, Ianunzio JR. Artificial intelligence in orthopedic surgery: evolution, current state and future directions. Arthroplasty 2022;4:9.

8. Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med 2019;380:1347-58.

9. Handelman GS, Kok HK, Chandra RV, Razavi AH, Lee MJ, Asadi H. eDoctor: machine learning and the future of medicine. J Intern Med 2018;284:603-19.

10. Kanevsky J, Corban J, Gaster R, Kanevsky A, Lin S, Gilardino M. Big data and machine learning in plastic surgery: a new frontier in surgical innovation. Plast Reconstr Surg 2016;137:890e-7e.

11. Schwarzer G, Vach W, Schumacher M. On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology. Statist Med 2000;19:541-61.

12. Lee JG, Jun S, Cho YW, et al. Deep learning in medical imaging: general overview. Korean J Radiol 2017;18:570-84.

13. Nadkarni PM, Ohno-Machado L, Chapman WW. Natural language processing: an introduction. J Am Med Inform Assoc 2011;18:544-51.

14. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med 2019;25:44-56.

15. Patel R, Tseng CC, Choudhry HS, Lemdani MS, Talmor G, Paskhover B. Applying machine learning to determine popular patient questions about mentoplasty on social media. Aesthetic Plast Surg 2022;46:2273-9.

16. Levites HA, Thomas AB, Levites JB, Zenn MR. The use of emotional artificial intelligence in plastic surgery. Plast Reconstr Surg 2019;144:499-504.

17. Boczar D, Sisti A, Oliver JD, et al. Artificial intelligent virtual assistant for plastic surgery patient’s frequently asked questions: a pilot study. Ann Plast Surg 2020;84:e16-21.

18. Chartier C, Watt A, Lin O, Chandawarkar A, Lee J, Hall-Findlay E. BreastGAN: artificial intelligence-enabled breast augmentation simulation. Aesthet Surg J Open Forum 2022;4:ojab052.

19. Chinski H, Lerch R, Tournour D, Chinski L, Caruso D. An artificial intelligence tool for image simulation in rhinoplasty. Facial Plast Surg 2022;38:201-6.

20. Gunes H, Piccardi M. Assessing facial beauty through proportion analysis by image processing and supervised learning. Int J Hum Comput Stud 2006;64:1184-99.

21. Crystal DT, Cuccolo NG, Ibrahim AMS, Furnas H, Lin SJ. Photographic and video deepfakes have arrived: how machine learning may influence plastic surgery. Plast Reconstr Surg 2020;145:1079-86.

22. Phillips M, Marsden H, Jaffe W, et al. Assessment of accuracy of an artificial intelligence algorithm to detect melanoma in images of skin lesions. JAMA Netw Open 2019;2:e1913436.

23. Mendoza CS, Safdar N, Okada K, Myers E, Rogers GF, Linguraru MG. Personalized assessment of craniosynostosis via statistical shape modeling. Med Image Anal 2014;18:635-46.

24. Bhalodia R, Dvoracek LA, Ayyash AM, Kavan L, Whitaker R, Goldstein JA. Quantifying the severity of metopic craniosynostosis: a pilot study application of machine learning in craniofacial surgery. J Craniofac Surg 2020;31:697-701.

25. Ferry Q, Steinberg J, Webber C, et al. Diagnostically relevant facial gestalt information from ordinary photos. Elife 2014;3:e02020.

26. Kiranantawat K, Sitpahul N, Taeprasartsit P, et al. The first smartphone application for microsurgery monitoring: silpaRamanitor. Plast Reconstr Surg 2014;134:130-9.

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

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

29. Turner AE, Abu-Ghname A, Davis MJ, Ali K, Winocour S. Role of simulation and artificial intelligence in plastic surgery training. Plast Reconstr Surg 2020;146:390e-1e.

30. Grenda TR, Pradarelli JC, Dimick JB. Using surgical video to improve technique and skill. Ann Surg 2016;264:32-3.

31. Robnik-šikonja M, Cukjati D, Kononenko I. Comprehensible evaluation of prognostic factors and prediction of wound healing. Artif Intell Med 2003;29:25-38.

32. Yeong EK, Hsiao TC, Chiang HK, Lin CW. Prediction of burn healing time using artificial neural networks and reflectance spectrometer. Burns 2005;31:415-20.

33. Estahbanati HK, Bouduhi N. Role of artificial neural networks in prediction of survival of burn patients-a new approach. Burns 2002;28:579-86.

34. Kuo PJ, Wu SC, Chien PC, et al. Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer. Oncotarget 2018;9:13768-82.

35. Liao H, Yan Y, Dai W, Fan P. Age estimation of face images based on CNN and divide-and-rule strategy. Math Model Eng Probl 2018;2018:1-8.

36. Patcas R, Bernini DAJ, Volokitin A, Agustsson E, Rothe R, Timofte R. Applying artificial intelligence to assess the impact of orthognathic treatment on facial attractiveness and estimated age. Int J Oral Maxillofac Surg 2019;48:77-83.

37. Iyer TKR, Nersisson R, Zhuang Z, Joseph Raj AN, Refayee I. Machine learning-based facial beauty prediction and analysis of frontal facial images using facial landmarks and traditional image descriptors. Comput Intell Neurosci 2021;2021:4423407.

38. Khetpal S, Peck C, Parsaei Y, et al. Perceived age and attractiveness using facial recognition software in rhinoplasty patients: a proof-of-concept study. J Craniofac Surg 2022;33:1540-4.

39. Dorfman R, Chang I, Saadat S, Roostaeian J. Making the subjective objective: machine learning and rhinoplasty. Aesthet Surg J 2020;40:493-8.

40. Patcas R, Timofte R, Volokitin A, et al. Facial attractiveness of cleft patients: a direct comparison between artificial-intelligence-based scoring and conventional rater groups. Eur J Orthod 2019;41:428-33.

41. Boonipat T, Asaad M, Lin J, Glass GE, Mardini S, Stotland M. Using artificial intelligence to measure facial expression following facial reanimation surgery. Plast Reconstr Surg 2020;146:1147-50.

42. Dusseldorp JR, Guarin DL, van Veen MM, Jowett N, Hadlock TA. In the eye of the beholder: changes in perceived emotion expression after smile reanimation. Plast Reconstr Surg 2019;144:457-71.

43. Chen K, Lu SM, Cheng R, et al. Facial recognition neural networks confirm success of facial feminization surgery. Plast Reconstr Surg 2020;145:203-9.

44. Piwek L, Ellis DA, Andrews S, Joinson A. The rise of consumer health wearables: promises and barriers. PLoS Med 2016;13:e1001953.

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

46. Lepri B, Oliver N, Pentland A. Ethical machines: the human-centric use of artificial intelligence. iScience 2021;24:102249.

47. Keskinbora KH. Medical ethics considerations on artificial intelligence. J Clin Neurosci 2019;64:277-82.

48. Maddox TM, Rumsfeld JS, Payne PRO. Questions for artificial intelligence in health care. JAMA 2019;321:31-2.

49. Liu J. Artificial intelligence is still far from truly revolutionizing plastic surgery. Plast Reconstr Surg 2020;146:390e.

Plastic and Aesthetic Research
ISSN 2349-6150 (Online)   2347-9264 (Print)

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/