REFERENCES
1. Ethics guidelines for trustworthy AI. Available from: https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai. [Last accessed on 15 May 2023].
2. Top 9 ethical issues in artificial intelligence. Available from: https://www.weforum.org/agenda/2016/10/top-10-ethical-issues-in-artificial-intelligence/. [Last accessed on 15 May 2023].
3. Bostrom N. Ethical issues in advanced artificial intelligence. In: Routledge, ed. Machine Ethics and Robot Ethics 2017. Available from: https://www.taylorfrancis.com/chapters/edit/10.4324/9781003074991-7/ethical-issues-advanced-artificial-intelligence-nick-bostrom. [Last accessed on 15 May 2023].
4. Gumbs AA, Alexander F, Karcz K, et al. White paper: definitions of artificial intelligence and autonomous actions in clinical surgery. Art Int Surg 2022;2:93-100.
5. Kessel R. British medical association: 1988, philosophy & practice of medical ethics, B.M. A., London, 94 pp. plus appendices, etc., 9.50 (paper). J Med Philos 1989;14:709-10.
6. Holm S. Principles of biomedical ethics, 5th edn. Beauchamp T L, Childress J F. Oxford University Press, 2001, £19.95, pp 454. ISBN 0-19-514332-9. 2002;28:332-332. Available from: https://jme.bmj.com/content/28/5/332.2. [Last accessed on 15 May 2023].
7. Regulation (EU) 2017/745 of the european parliament and of the council of 5 April 2017. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32017R0745. [Last accessed on 15 May 2023].
8. Proposal for a regulation of the european parliament and of the council laying down harmonised rules on artificial intelligence (artificial intelligence act) and amending certain union legislative acts. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52021PC0206. [Last accessed on 15 May 2023].
9. Statement from FDA commissioner scott gottlieb, M.D. on steps toward a new, tailored review framework for artificial intelligence-based medical devices. Available from: https://www.fda.gov/news-events/press-announcements/statement-fda-commissioner-scott-gottlieb-md-steps-toward-new-tailored-review-framework-artificial. [Last accessed on 15 May 2023].
10. McCulloch P, Altman DG, Campbell WB, et al. Balliol Collaboration. No surgical innovation without evaluation: the IDEAL recommendations. Lancet 2009;374:1105-12.
11. Amin F, Abbasi R, Mateen A, Ali Abid M, Khan S. A step toward next-generation advancements in the internet of things technologies. Sensors 2022;22:8072.
12. Complete guide to GDPR compliance. Available from: https://gdpr.eu/. [Last accessed on 15 May 2023].
13. HIPAA & your health rights. Available from: https://www.hhs.gov/programs/hipaa/index.html. [Last accessed on 15 May 2023].
14. AI ethics (AI code of ethics). Available from: https://www.techtarget.com/whatis/definition/AI-code-of-ethics. [Last accessed on 15 May 2023].
15. Unethical use of artificial intelligence. Available from: https://lasserouhiainen.com/unethical-use-of-artificial-intelligence/. [Last accessed on 15 May 2023].
16. Bias in AI and machine learning: some recent examples (OR cases in point). Available from: https://www.lexalytics.com/blog/bias-in-ai-machine-learning/. [Last accessed on 15 May 2023].
17. Should AI be fair and non-discriminative. Available from: https://ethics-of-ai.mooc.fi/chapter-6/3-discrimination-and-biases. [Last accessed on 15 May 2023].
18. 3 essential steps for AI ethics. Available from: https://www.sas.com/en_us/insights/articles/analytics/artificial-intelligence-ethics.html. [Last accessed on 15 May 2023].
19. What are the risks of artificial intelligence? Available from: https://www.linkedin.com/pulse/what-risks-artificial-intelligence-philip-mckeown. [Last accessed on 15 May 2023].
20. Top 7 challenges in artificial intelligence in 2023. Available from: https://www.upgrad.com/blog/top-challenges-in-artificial-intelligence/. [Last accessed on 15 May 2023].
21. Is the way you think biased? Here are 3 common mistakes to watch out for. Available from: https://www.weforum.org/agenda/2022/04/cognitive-biases-three-common-types-illustrated/. [Last accessed on 15 May 2023].
22. Sparrow R, Hatherley J. The promise and perils of AI in medicine. Available from: https://www.researchgate.net/publication/344879321_The_promise_and_perils_of_AI_in_medicine. [Last accessed on 15 May 2023].
23. Amann J, Blasimme A, Vayena E, Frey D, Madai VI. Precise4Q consortium. Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC Med Inform Decis Mak 2020;20:310.
24. Rashidian N, Hilal MA. Applications of machine learning in surgery: ethical considerations. Art Int Surg 2022;2:18-23.
25. Gumbs AA, Perretta S, d’Allemagne B, Chouillard E. What is artificial intelligence surgery? Art Int Surg 2021;1:1-10.
26. Boutros C, Singh V, Ocuin L, Marks JM, Hashimoto DA. Artificial intelligence in hepatopancreaticobiliary surgery - promises and perils. Art Int Surg 2022;2:213-23.
27. European Commission. The 2030 agenda for sustainable development and SDGs. Available from: https://commission.europa.eu/strategy-and-policy/international-strategies/sustainable-development-goals/eu-and-united-nations-common-goals-sustainable-future_en. [Last accessed on 18 May 2023].
28. Stypińska J, Franke A. AI revolution in healthcare and medicine and the (re-)emergence of inequalities and disadvantages for ageing population. Front Sociol 2022;7:1038854.
29. d’Elia A, Gabbay M, Rodgers S, et al. Artificial intelligence and health inequities in primary care: a systematic scoping review and framework. Fam Med Community Health 2022;10:e001670.
30. Gupta M, Parra CM, Dennehy D. Questioning racial and gender bias in AI-based recommendations: do espoused national cultural values matter? Inf Syst Front 2022;24:1465-81.
31. Elwyn G, Nelson E, Hager A, Price A. Coproduction: when users define quality. BMJ Qual Saf 2020;29:711-6.
32. Kerasidou A. Ethics of artificial intelligence in global health: Explainability, algorithmic bias and trust. J Oral Biol Craniofac Res 2021;11:612-4.
33. Wahl B, Cossy-Gantner A, Germann S, Schwalbe NR. Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings? BMJ Glob Health 2018;3:e000798.
34. Cobianchi L, Verde JM, Loftus TJ, et al. Artificial intelligence and surgery: ethical dilemmas and open issues. J Am Coll Surg 2022;235:268-75.
35. Myers SP, Dasari M, Brown JB, et al. Effects of gender bias and stereotypes in surgical training: a randomized clinical trial. JAMA Surg 2020;155:552-60.
36. Yuce TK, Turner PL, Glass C, et al. National evaluation of racial/ethnic discrimination in US surgical residency programs. JAMA Surg 2020;155:526-8.
37. Ferrari L, Mari V, De Santi G, et al. Early barriers to career progression of women in surgery and solutions to improve them: a systematic scoping review. Ann Surg 2022;276:246-55.
38. Karnick A, Limberg J, Bagautdinov I, et al. Can general surgery interns accurately measure their own technical skills? Analysis of cognitive bias in surgical residents' self-assessments. Surgery 2021;170:1353-8.
39. Dill-Macky A, Hsu CH, Neumayer LA, Nfonsam VN, Turner AP. The role of implicit bias in surgical resident evaluations. J Surg Educ 2022;79:761-8.
40. Voss M, Swart O, Abel L, Mahtani K. Capacity-building partnerships for surgical post-graduate training in low- and middle-income countries: a scoping review of the literature with exploratory thematic synthesis. Health Policy Plan 2021;35:1385-412.
41. Mirchi N, Bissonnette V, Yilmaz R, Ledwos N, Winkler-Schwartz A, Del Maestro RF. The virtual operative assistant: an explainable artificial intelligence tool for simulation-based training in surgery and medicine. PLoS One 2020;15:e0229596.
42. Anvari M, Manoharan B, Barlow K. From telementorship to automation. J Surg Oncol 2021;124:246-9.
43. Reiley CE, Lin HC, Yuh DD, Hager GD. Review of methods for objective surgical skill evaluation. Surg Endosc 2011;25:356-66.
44. Madani A, Namazi B, Altieri MS, et al. Artificial intelligence for intraoperative guidance: using semantic segmentation to identify surgical anatomy during laparoscopic cholecystectomy. Ann Surg 2022;276:363-9.
45. Asghar MS, Zaman BS, Zahid A. Past, present, and future of surgical simulation and perspective of a developing country: A narrative review. J Pak Med Assoc 2021;71:2770-6.
46. Martinerie L, Rasoaherinomenjanahary F, Ronot M, et al. Health care simulation in developing countries and low-resource situations. J Contin Educ Health Prof 2018;38:205-12.
47. Rangel EL, Smink DS, Castillo-Angeles M, et al. Pregnancy and motherhood during surgical training. JAMA Surg 2018;153:644-52.
48. Bissonnette V, Mirchi N, Ledwos N, Alsidieri G, Winkler-Schwartz A, Del Maestro RF, Neurosurgical Simulation & artificial intelligence learning centre. Artificial intelligence distinguishes surgical training levels in a virtual reality spinal task. J Bone Joint Surg Am 2019;101:e127.
