ArticleFrontiers in robotics and AI2022
Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty.
Article in Frontiers in robotics and AI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 38 papers, 3 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 64 citations in OpenAlex.
- 3D imaging-based AI models outperform demographic models and excel in tibial sizing compared with 2D models in total knee arthroplasty planning: A systematic review.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Pooled it
- Artificial intelligence in total and unicompartmental knee arthroplasty.BMC musculoskeletal disorders · 2024Pooled it
- Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2024Pooled it
- Functional and electrophysiological outcomes following surgical treatment of cubitus varus associated with tardy ulnar nerve palsy: A case series.Shoulder & elbow · 2026Article
- Artificial Intelligence Applications in Implant Positioning, Dislocation Risk Prediction, and Surgical Indications in Orthopaedic Surgery.Bioengineering (Basel, Switzerland) · 2026Review
- CT-based 3D planning-supported stem-free screw-cement augmentation versus 2D radiograph-planned short-stem reconstruction for AORI type I-II medial tibial defects in TKA: a two-year retrospective study.Journal of orthopaedic surgery and research · 2026Article
- Artificial Intelligence in Orthopaedics: Clinical Performance, Limitations, and Translational Readiness-A Review.Journal of clinical medicine · 2026Review
- The Application of artificial intelligence in periprosthetic joint infection.Journal of advanced research · 2026Review
- Artificial intelligence and robotic technologies redefining precision and personalization in orthopedic surgery: a narrative review.Frontiers in bioengineering and biotechnology · 2026Review
- Review
- Artificial Intelligence Applications in Musculoskeletal Imaging.Current reviews in musculoskeletal medicine · 2025Review
- Artificial intelligence in total knee arthroplasty: clinical applications and implications.Knee surgery & related research · 2025Review
- Leveraging data to transform surgical outcomes and precision in orthopaedics.Journal of clinical orthopaedics and trauma · 2025Review
- Joint line elevation after TKA is higher in patients with metaphyseal deformity: a prospective study.Archives of orthopaedic and trauma surgery · 2025Article
- Review
- The revolutionary impact of artificial intelligence in orthopedics: comprehensive review of current benefits and challenges.Journal of robotic surgery · 2025Review
- Use of Artificial Intelligence on Imaging and Preoperatory Planning of the Knee Joint: A Scoping Review.Medicina (Kaunas, Lithuania) · 2025Article
- A review of novel methods to assist digital planning and execution of osteotomy for upper limb deformities.Biomedical engineering online · 2025Review
- Comparison of an AI-driven planning tool and manual radiographic measurements in total knee arthroplasty.Computational and structural biotechnology journal · 2025Article
- Fully automated workflow for designing patient-specific orthopaedic implants: Application to total knee arthroplasty.PloS one · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Previous studies have shown that the manufacturer's default preoperative plans for total knee arthroplasty with patient-specific guides require frequent, time-consuming changes by the surgeon. Currently, no research has been done on predicting preoperative plans for orthopedic surgery using machine learning. Therefore, this study aims to evaluate whether artificial intelligence (AI) driven planning tools can create surgeon and patient-specific preoperative plans that require fewer changes by the surgeon. A dataset of 5409 preoperative plans, including the manufacturer's default and the plans corrected by 39 surgeons, was collected. Features were extracted from the preoperative plans that describe the implant sizes, position, and orientation in a surgeon- and patient-specific manner. Based on these features, non-linear regression models were employed to predict the surgeon's corrected preoperative plan. The average number of corrections a surgeon has to make to the preoperative plan generated using AI was reduced by 39.7% compared to the manufacturer's default plan. The femoral and tibial implant size in the manufacturer's plan was correct in 68.4% and 73.1% of the cases, respectively, while the AI-based plan was correct in 82.2% and 85.0% of the cases, respectively, compared to the surgeon approved plan. Our method successfully demonstrated the use of machine learning to create preoperative plans in a surgeon- and patient-specific manner for total knee arthroplasty.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.