REFERENCES
1. Stirling ER, Lewis TL, Ferran NA. Surgical skills simulation in trauma and orthopaedic training. J Orthop Surg Res. 2014;9:126.
2. Mackenzie CF, Tisherman SA, Shackelford S, Sevdalis N, Elster E, Bowyer MW. Efficacy of trauma surgery technical skills training courses. J Surg Educ. 2019;76:832-43.
3. Sadagopan NS, Prasad D, Jain R, Ahuja C, Dahdaleh NS, El Tecle NE. Beyond AI and robotics: the dawn of surgical automation in spine surgery. Art Int Surg. 2024;4:387-400.
4. Moran ME, George R. Past present and future of simulation in trauma. In: StatPearls [Internet]. Treasure Island: StatPearls Publishing; 2025.
5. Davies J, Pilling R, Dimri R, Chakrabarty G. Expert practical operative skills teaching in Trauma and Orthopaedics at a nominal cost. Surgeon. 2012;10:330-3.
6. Suárez ADP, Cepeda MP. Factores que intervienen en el aprendizaje de ortopedia y traumatología en estudiantes de instrumentación quirúrgica en una institución de educación superior en la ciudad de Bogotá. Educación Médica. 2021;22:323-9. (in Spanish).
7. Mehta S, Smith JM. Resources for your career in orthopaedic traumatology: what can the OTA do for you? J Orthop Trauma. 2012;26 Suppl 1:S25-6.
8. Maffulli N, Rodriguez HC, Stone IW, et al. Artificial intelligence and machine learning in orthopedic surgery: a systematic review protocol. J Orthop Surg Res. 2020;15:478.
9. Fuleihan AA, Menta AK, Azad TD, et al. Navigating artificial intelligence in spine surgery: implementation and optimization across the care continuum. Art Int Surg. 2024;4:288-95.
10. Cobianchi L, Piccolo D, Dal Mas F, et al; Team Dynamics Study Group. Correction: Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey. World J Emerg Surg. 2023;18:22.
11. De Simone B, Abu-Zidan FM, Gumbs AA, et al. Knowledge, attitude, and practice of artificial intelligence in emergency and trauma surgery, the ARIES project: an international web-based survey. World J Emerg Surg. 2022;17:10.
12. Shah RM, Wong C, Arpey NC, Patel AA, Divi SN. A surgeon’s guide to understanding artificial intelligence and machine learning studies in orthopaedic surgery. Curr Rev Musculoskelet Med. 2022;15:121-32.
13. Checcucci E, De Cillis S, Amparore D, et al. Artificial intelligence alert systems during robotic surgery: a new potential tool to improve the safety of the intervention. Urol Video J. 2023;18:100221.
14. Zhu Z, Zheng G, Zhang C. Development and clinical application of robot-assisted technology in traumatic orthopedics. Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi. 2022;36:915-22. (in Chinese).
15. Salimi M, Parry JA, Shahrokhi R, Mosalamiaghili S. Application of artificial intelligence in trauma orthopedics: limitation and prospects. World J Clin Cases. 2023;11:4231-40.
16. Powling AS, Lisacek-Kiosoglous AB, Fontalis A, Mazomenos E, Haddad FS. Unveiling the potential of artificial intelligence in orthopaedic surgery. Br J Hosp Med. 2023;84:1-5.
17. Jeyaraman M, Ratna HVK, Jeyaraman N, Venkatesan A, Ramasubramanian S, Yadav S. Leveraging artificial intelligence and machine learning in regenerative orthopedics: a paradigm shift in patient Care. Cureus. 2023;15:e49756.
18. Civaner MM, Uncu Y, Bulut F, Chalil EG, Tatli A. Artificial intelligence in medical education: a cross-sectional needs assessment. BMC Med Educ. 2022;22:772.
19. Ejaz H, McGrath H, Wong BL, Guise A, Vercauteren T, Shapey J. Artificial intelligence and medical education: a global mixed-methods study of medical students’ perspectives. Digit Health. 2022;8:20552076221089099.
20. Boillat T, Nawaz FA, Rivas H. Readiness to embrace artificial intelligence among medical doctors and students: questionnaire-based study. JMIR Med Educ. 2022;8:e34973.
21. Bhattad PB, Jain V. Artificial intelligence in modern medicine - the evolving necessity of the present and role in transforming the future of medical care. Cureus. 2020;12:e8041.
22. Busch F, Adams LC, Bressem KK. Biomedical ethical aspects towards the implementation of artificial intelligence in medical education. Med Sci Educ. 2023;33:1007-12.
23. Krive J, Isola M, Chang L, Patel T, Anderson M, Sreedhar R. Grounded in reality: artificial intelligence in medical education. JAMIA Open. 2023;6:ooad037.
25. Narayanan S, Ramakrishnan R, Durairaj E, Das A. Artificial intelligence revolutionizing the field of medical education. Cureus. 2023;15:e49604.
26. Boddu S, Subramanian A, Sattar ZS, et al. Utility of artificial intelligence-based tool for medical education during rounds in the ICU. CHEST. 2023;164:A1809.
27. Beam AL, Drazen JM, Kohane IS, Leong TY, Manrai AK, Rubin EJ. Artificial intelligence in medicine. N Engl J Med. 2023;388:1220-1.
28. Wartman SA, Combs CD. Reimagining medical education in the age of AI. AMA J Ethics. 2019;21:E146-152.
29. Aggarwal R, Mytton OT, Derbrew M, et al. Training and simulation for patient safety. Qual Saf Health Care. 2010;19 Suppl 2:i34-43.
30. Loftus TJ, Filiberto AC, Balch J, et al. Intelligent, autonomous machines in surgery. J Surg Res. 2020;253:92-9.
31. Vitiello V, Lee SL, Cundy TP, Yang GZ. Emerging robotic platforms for minimally invasive surgery. IEEE Rev Biomed Eng. 2013;6:111-26.
32. Bilgic E, Gorgy A, Yang A, et al. Exploring the roles of artificial intelligence in surgical education: a scoping review. Am J Surg. 2022;224:205-16.
33. Misir A. Artificial intelligence in orthopedic trauma: a comprehensive review. Injury. 2025;56:112570.
34. Milella F, Famiglini L, Banfi G, Cabitza F. Application of machine learning to improve appropriateness of treatment in an orthopaedic setting of personalized medicine. J Pers Med. 2022;12:1706.
35. Tian C, Gao Y, Rui C, Qin S, Shi L, Rui Y. Artificial intelligence in orthopaedic trauma. EngMedicine. 2024;1:100020.
36. Mienye ID, Obaido G, Jere N, et al. A survey of explainable artificial intelligence in healthcare: concepts, applications, and challenges. Inform Med Unlocked. 2024;51:101587.
37. Hildt E. What is the role of explainability in medical artificial intelligence? Bioengineering. 2025;12:375.
38. Joseph J. Algorithmic bias in public health AI: a silent threat to equity in low-resource settings. Front Public Health. 2025;13:1643180.
39. Hussain SA, Bresnahan M, Zhuang J. Can artificial intelligence revolutionize healthcare in the Global South? Digit Health. 2025;11:20552076251348024.
40. Al-Saadawi A, Tehranchi S, Ahmed S, Nzeako OJ. Exploring the current applications of artificial intelligence in orthopaedic surgical training: a systematic scoping review. Cureus. 2025;17:e81671.
41. Appel G, Shahzad AT, Reopelle K, DiDonato S, Rusnack F, Papanagnou D. Exploring medical student experiences of trauma in the emergency department: opportunities for trauma-informed medical education. West J Emerg Med. 2024;25:828-37.
42. Tian C, Chen X, Zhu H, Qin S, Shi L, Rui Y. Application and prospect of machine learning in orthopaedic trauma. Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi. 2023;37:1562-8. (in Chinese).
43. Cabitza F, Locoro A, Banfi G. Machine learning in orthopedics: a literature review. Front Bioeng Biotechnol. 2018;6:75.
44. Spitler CA. Life long learning: the attending and educator in orthopedic trauma. Orthop Clin North Am. 2021;52:53-9.
45. Mackenzie CF, Garofalo E, Shackelford S, et al. Using an individual procedure score before and after the advanced surgical skills exposure for trauma course training to benchmark a hemorrhage-control performance metric. J Surg Educ. 2015;72:1278-89.
46. Kalraiya A, Buddhdev P. The TROJAN project: creating a customized international orthopedic training program for junior doctors. Orthop Rev. 2015;7:5750.
47. Hopkins L, Robinson DBT, Brown C, et al. Trauma and orthopedic surgery curriculum concordance: an operative learning curve trajectory perspective. J Surg Educ. 2019;76:1569-78.
48. Cannada LK. Orthopaedic trauma education: how many to train and how to pay for it? J Orthop Trauma. 2014;28 Suppl 10:S23-6.
49. Taylor BC, Fowler TT. Analysis of the trauma section of the orthopaedic in-training examination. Orthopedics. 2011;34:e261-6.
50. Haider Z, Hunter A. Orthopedic trainees’ perceptions of the educational value of daily trauma meetings. J Surg Educ. 2020;77:991-8.
51. Lisacek-Kiosoglous AB, Powling AS, Fontalis A, Gabr A, Mazomenos E, Haddad FS. Artificial intelligence in orthopaedic surgery. Bone Joint Res. 2023;12:447-54.
52. Knopp MI, Warm EJ, Weber D, et al. AI-enabled medical education: threads of change, promising futures, and risky realities across four potential future worlds. JMIR Med Educ. 2023;9:e50373.
53. Mennella C, Maniscalco U, De Pietro G, Esposito M. Ethical and regulatory challenges of AI technologies in healthcare: a narrative review. Heliyon. 2024;10:e26297.
54. Pressman SM, Borna S, Gomez-Cabello CA, Haider SA, Haider C, Forte AJ. AI and ethics: a systematic review of the ethical considerations of large language model use in surgery research. Healthcare. 2024;12:825.
55. Berdahl CT, Baker L, Mann S, Osoba O, Girosi F. Strategies to improve the impact of artificial intelligence on health equity: scoping review. JMIR AI. 2023;2:e42936.
56. Badr J, Motulsky A, Denis JL. Digital health technologies and inequalities: a scoping review of potential impacts and policy recommendations. Health Policy. 2024;146:105122.
57. Dychiao RG, Nazer L, Mlombwa D, Celi LA. Artificial intelligence and global health equity. BMJ. 2024;387:q2194.
58. Zuhair V, Babar A, Ali R, et al. Exploring the impact of artificial intelligence on global health and enhancing healthcare in developing nations. J Prim Care Community Health. 2024;15:21501319241245847.
59. Dijkstra H, van de Kuit A, de Groot TM, et al; Machine Learning Consortium. Systematic review of machine-learning models in orthopaedic trauma. Bone Jt Open. 2024;5:9-19.
60. Debs P, Fayad LM. The promise and limitations of artificial intelligence in musculoskeletal imaging. Front Radiol. 2023;3:1242902.
61. Alzubaidi L, Al-Dulaimi K, Salhi A, et al. Comprehensive review of deep learning in orthopaedics: applications, challenges, trustworthiness, and fusion. Artif Intell Med. 2024;155:102935.
62. Tafat W, Budka M, Mcdonald D, Wainwright TW. Artificial intelligence in orthopaedic surgery: A comprehensive review of current innovations and future directions. Comput Struct Biotechnol Rep. 2024;1:100006.
63. Koçak B, Ponsiglione A, Stanzione A, et al. Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects. Diagn Interv Radiol. 2025;31:75-88.






