Artificial Intelligence in Revision Total Knee Arthroplasty
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-60445-4_16
Reference11 articles.
1. Rodriguez-Merchan EC. The current role of the virtual elements of artificial intelligence in total knee arthroplasty. EFORT Open Rev. 2022;7(7):491–7. https://doi.org/10.1530/EOR-21-0107.
2. Lau LCM, Chui ECS, Man GCW, Xin Y, Ho KKW, Mak KKK, et al. A novel image-based machine learning model with superior accuracy and predictability for knee arthroplasty loosening detection and clinical decision making. J Orthop Translat. 2022;36:177–83. https://doi.org/10.1016/j.jot.2022.07.004.
3. Karlin EA, Lin CC, Meftah M, Slover JD, Schwarzkopf R. The impact of machine learning on total joint arthroplasty patient outcomes: a systemic review. J Arthroplast. 2023;38(10):2085–95. https://doi.org/10.1016/j.arth.2022.10.039.
4. Shah RF, Bini SA, Martinez AM, Pedoia V, Vail TP. Incremental inputs improve the automated detection of implant loosening using machine-learning algorithms. Bone Joint J. 2020;102-B(6_Supple_A):101–6. https://doi.org/10.1302/0301-620X.102B6.BJJ-2019-1577.R1.
5. Klemt C, Uzosike AC, Harvey MJ, Laurencin S, Habibi Y, Kwon YM. Neural network models accurately predict discharge disposition after revision total knee arthroplasty? Knee Surg Sports Traumatol Arthrosc. 2022;30(8):2591–9. https://doi.org/10.1007/s00167-021-06778-3.
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