Page 22 - Read Online
P. 22
Page 267 Collins et al. Art Int Surg. 2025;5:254-69 https://dx.doi.org/10.20517/ais.2024.92
Ethical approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Copyright
© The Author(s) 2025.
REFERENCES
1. HerniaSurge Group. International guidelines for groin hernia management. Hernia. 2018;22:1-165. DOI PubMed PMC
2. Allied Market Research. Hernia repair devices and consumables market size, share, competitive landscape and trend analysis report, by
product, surgery type and hernia type : global opportunity analysis and industry forecast, 2020-2027. Available from: https://www.
alliedmarketresearch.com/hernia-repair-devices-market. [Last accessed on 17 Apr 2025].
3. Wang F, Ma B, Ma Q, Liu X. Global, regional, and national burden of inguinal, femoral, and abdominal hernias: a systematic analysis
of prevalence, incidence, deaths, and DALYs with projections to 2030. Int J Surg. 2024;110:1951-67. DOI PubMed PMC
4. Smith JM, Kapur SK, Mericli AF, Baumann DP, Butler CE. Parastomal hernia repair. Plast Aesthet Res. 2022;9:10. DOI
5. Köckerling F, Sheen AJ, Berrevoet F, et al. The reality of general surgery training and increased complexity of abdominal wall hernia
surgery. Hernia. 2019;23:1081-91. DOI PubMed PMC
6. Tuma F, Lopez RA, Varacallo MA. Anatomy, abdomen and pelvis: inguinal region (inguinal canal). Available from: http://www.ncbi.
nlm.nih.gov/books/NBK470204/. [Last accessed on 17 Apr 2025].
7. Roos MM, Bakker WJ, Schouten N, et al. Higher recurrence rate after endoscopic totally extraperitoneal (TEP) inguinal hernia repair
with ultrapro lightweight mesh: 5-year results of a randomized controlled trial (TULP-trial). Ann Surg. 2018;268:241-6. DOI
8. Wu F, Zhang X, Liu Y, Cao D, Yu Y, Ma Y. Lightweight mesh versus heavyweight mesh for laparo-endoscopic inguinal hernia repair:
a systematic review and meta-analysis. Hernia. 2020;24:31-9. DOI
9. Bakker WJ, Aufenacker TJ, Boschman JS, Burgmans JPJ. Heavyweight mesh is superior to lightweight mesh in laparo-endoscopic
inguinal hernia repair: a meta-analysis and trial sequential analysis of randomized controlled trials. Ann Surg. 2021;273:890-9. DOI
PubMed
10. Levy AS, Bernstein JL, Celie KB, Spector JA. Quantifying fascial tension in ventral hernia repair and component separation. Hernia.
2021;25:107-14. DOI PubMed
11. Dietz UA, Kudsi OY, Gokcal F, et al. Excess body weight and abdominal hernia. Visc Med. 2021;37:246-53. DOI PubMed PMC
12. de Beaux A, Becker S, Parent T, et al. Hernia Basecamp - a free to use, online hernia learning platform. Analysis of its use since
launch in June 2021. J Abdom Wall Surg. 2023;2:11803. DOI PubMed PMC
13. Xu Y, Saiding Q, Zhou X, Wang J, Cui W, Chen X. Electrospun fiber-based immune engineering in regenerative medicine. Smart
Med. 2024;3:e20230034. DOI PubMed PMC
14. Murphy BL, Ubl DS, Zhang J, Habermann EB, Farley DR, Paley K. Trends of inguinal hernia repairs performed for recurrence in the
United States. Surgery. 2018;163:343-50. DOI PubMed
15. Palser TR, Swift S, Williams RN, Bowrey DJ, Beckingham IJ. Variation in outcomes and use of laparoscopy in elective inguinal
hernia repair. BJS Open. 2019;3:466-75. DOI PubMed PMC
16. Takeuchi M, Collins T, Lipps C, et al. Towards automatic verification of the critical view of the myopectineal orifice with artificial
intelligence. Surg Endosc. 2023;37:4525-34. DOI
17. Takeuchi M, Collins T, Ndagijimana A, et al. Automatic surgical phase recognition in laparoscopic inguinal hernia repair with
artificial intelligence. Hernia. 2022;26:1669-78. DOI
18. LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436-44. DOI PubMed
19. Chan H, Samala RK, Hadjiiski LM, Zhou C. Deep learning in medical image analysis. In: Lee G, Fujita H, editors. Deep learning in
medical image analysis. Cham: Springer International Publishing; 2020. pp. 3-21. DOI PubMed PMC
20. De Coster M, Shterionov D, Van Herreweghe M, et al. Machine translation from signed to spoken languages: state of the art and
challenges. Univ Access Inf Soc. 2024;23:1305-31. DOI
21. Cao H, Tan C, Gao Z, et al. A survey on generative diffusion models. IEEE Trans Knowl Data Eng. 2024;36:2814-30. DOI
22. Bengesi S, El-Sayed H, Sarker MK, Houkpati Y, Irungu J, Oladunni T. Advancements in generative AI: a comprehensive review of
GANs, GPT, autoencoders, diffusion model, and transformers. IEEE Access. 2024;12:69812-37. DOI
23. Liu C, Yu H. AI-empowered persuasive video generation: a survey. ACM Comput Surv. 2023;55:1-31. DOI
24. Ning Y, He S, Wu Z, Xing C, Zhang LJ. A review of deep learning based speech synthesis. Appl Sci. 2019;9:4050. DOI
25. ChatGPT. Available: https://chatgpt.com. [Last accessed on 17 Apr 2025].
26. Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH. nnU-Net: a self-configuring method for deep learning-based biomedical
image segmentation. Nat Methods. 2021;18:203-11. DOI PubMed
27. Abadi M, Agarwal A, Barham P, et al. TensorFlow: large-scale machine learning on heterogeneous distributed systems. arXiv 2016,

