Page 25 - Read Online
P. 25
Dababneh et al. Art Int Surg 2024;4:214-32 https://dx.doi.org/10.20517/ais.2024.50 Page 230
10. Loftus TJ, Tighe PJ, Filiberto AC, et al. Artificial intelligence and surgical decision-making. JAMA Surg 2020;155:148-58. DOI
PubMed PMC
11. Spoer DL, Kiene JM, Dekker PK, et al. A systematic review of artificial intelligence applications in plastic surgery: looking to the
future. Plast Reconstr Surg Glob Open 2022;10:e4608. DOI PubMed PMC
12. Dorfman R, Chang I, Saadat S, Roostaeian J. Making the subjective objective: machine learning and rhinoplasty. Aesthet Surg J
2020;40:493-8. DOI PubMed
13. Eldaly AS, Avila FR, Torres-Guzman RA, et al. Simulation and artificial intelligence in rhinoplasty: a systematic review. Aesthetic
Plast Surg 2022;46:2368-77. DOI PubMed
14. 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. DOI PubMed
15. Tricco AC, Lillie E, Zarin W, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern
Med 2018;169:467-73. DOI PubMed
16. Thibaut G, Dabbagh A, Liverneaux P. Does Google’s Bard Chatbot perform better than ChatGPT on the European hand surgery exam?
Int Orthop 2024;48:151-8. DOI PubMed
17. Arango SD, Flynn JC, Zeitlin J, et al. The performance of ChatGPT on the American society for surgery of the hand self-assessment
examination. Cureus 2024;16:e58950. DOI PubMed PMC
18. Ghanem D, Nassar JE, El Bachour J, Hanna T. ChatGPT earns American Board Certification in Hand Surgery. Hand Surg Rehabil
2024;43:101688. DOI PubMed
19. Crook BS, Park CN, Hurley ET, Richard MJ, Pidgeon TS. Evaluation of online artificial intelligence-generated information on
common hand procedures. J Hand Surg Am 2023;48:1122-7. DOI PubMed
20. Seth I, Sinkjær Kenney P, Bulloch G, Hunter-Smith DJ, Bo Thomsen J, Rozen WM. Artificial or augmented authorship? A
conversation with a chatbot on base of thumb arthritis. Plast Reconstr Surg Glob Open 2023;11:e4999. DOI PubMed PMC
21. Leypold T, Schäfer B, Boos A, Beier JP. Can AI think like a plastic surgeon? Evaluating GPT-4’s clinical judgment in reconstructive
procedures of the upper extremity. Plast Reconstr Surg Glob Open 2023;11:e5471. DOI PubMed PMC
22. Seth I, Xie Y, Rodwell A, et al. Exploring the role of a large language model on carpal tunnel syndrome management: an observation
study of ChatGPT. J Hand Surg Am 2023;48:1025-33. DOI PubMed
23. Seth I, Lim B, Xie Y, Hunter-Smith DJ, Rozen WM. Exploring the role of artificial intelligence chatbot on the management of
scaphoid fractures. J Hand Surg Eur Vol 2023;48:814-8. DOI PubMed
24. Ajmera P, Nischal N, Ariyaratne S, et al. Validity of ChatGPT-generated musculoskeletal images. Skeletal Radiol 2024;53:1583-93.
DOI PubMed
25. Olczak J, Fahlberg N, Maki A, et al. Artificial intelligence for analyzing orthopedic trauma radiographs. Acta Orthop 2017;88:581-6.
DOI PubMed PMC
26. Lee KC, Choi IC, Kang CH, et al. Clinical validation of an artificial intelligence model for detecting distal radius, ulnar styloid, and
scaphoid fractures on conventional wrist radiographs. Diagnostics 2023;13:1657. DOI PubMed PMC
27. Lindsey R, Daluiski A, Chopra S, et al. Deep neural network improves fracture detection by clinicians. Proc Natl Acad Sci U S A
2018;115:11591-6. DOI PubMed PMC
28. Cohen M, Puntonet J, Sanchez J, et al. Artificial intelligence vs. radiologist: accuracy of wrist fracture detection on radiographs. Eur
Radiol 2023;33:3974-83. DOI PubMed
29. Hardalaç F, Uysal F, Peker O, et al. Fracture detection in wrist x-ray images using deep learning-based object detection models.
Sensors 2022;22:1285. DOI PubMed PMC
30. Lysdahlgaard S. Utilizing heat maps as explainable artificial intelligence for detecting abnormalities on wrist and elbow radiographs.
Radiography 2023;29:1132-8. DOI PubMed
31. Alammar Z, Alzubaidi L, Zhang J, Li Y, Lafta W, Gu Y. Deep transfer learning with enhanced feature fusion for detection of
abnormalities in X-ray images. Cancers 2023;15:4007. DOI PubMed PMC
32. Jacques T, Cardot N, Ventre J, Demondion X, Cotten A. Commercially-available AI algorithm improves radiologists’ sensitivity for
wrist and hand fracture detection on X-ray, compared to a CT-based ground truth. Eur Radiol 2024;34:2885-94. DOI PubMed
33. Kim DH, MacKinnon T. Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks. Clin
Radiol 2018;73:439-45. DOI PubMed
34. Gan K, Xu D, Lin Y, et al. Artificial intelligence detection of distal radius fractures: a comparison between the convolutional neural
network and professional assessments. Acta Orthop 2019;90:394-400. DOI PubMed PMC
35. Thian YL, Li Y, Jagmohan P, Sia D, Chan VEY, Tan RT. Convolutional neural networks for automated fracture detection and
localization on wrist radiographs. Radiol Artif Intell 2019;1:e180001. DOI PubMed PMC
36. Oka K, Shiode R, Yoshii Y, Tanaka H, Iwahashi T, Murase T. Artificial intelligence to diagnosis distal radius fracture using biplane
plain X-rays. J Orthop Surg Res 2021;16:694. DOI PubMed PMC
37. Russe MF, Rebmann P, Tran PH, et al. AI-based X-ray fracture analysis of the distal radius: accuracy between representative
classification, detection and segmentation deep learning models for clinical practice. BMJ Open 2024;14:e076954. DOI PubMed
PMC
38. Zhang J, Li Z, Lin H, et al. Deep learning assisted diagnosis system: improving the diagnostic accuracy of distal radius fractures. Front
Med 2023;10:1224489. DOI PubMed PMC