ReviewDiagnostics (Basel, Switzerland)2024
Emerging Innovations in Preoperative Planning and Motion Analysis in Orthopedic Surgery.
Review in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
12 citing papers in PubMed.
- Combining Static Stance and Dynamic Gait Personalization to Improve the Accuracy of Patient-Specific Finite-Element Models for Hallux Valgus Foot.Annals of biomedical engineering · 2026Article
- Review
- Artificial intelligence in orthopaedics: Enhanced examinations, ambient intelligence and the future of clinical practice.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Review
- Development of a Deep Learning Model for Hip Arthroplasty Templating Using Anteroposterior Hip Radiograph.Journal of clinical medicine · 2025Article
- Integrating artificial intelligence into orthopedics: Opportunities, challenges, and future directions.Journal of hand and microsurgery · 2025Review
- Advances in Managing Pelvic Fractures in Polytrauma: A Comprehensive Review.Journal of clinical medicine · 2025Review
- Intra- and inter-observer reliabilities of cervical sagittal radiographic measurements among evaluators with different levels of training.Einstein (Sao Paulo, Brazil) · 2025Article
- The Clinical and Radiological Outcomes and Complications of Bilboquet Implant for Proximal Humerus Fractures: A Systematic Review.Journal of clinical medicine · 2024Review
- Review
- Mid-Term Clinical and Radiographic Results of Complex Hip Revision Arthroplasty Based on 3D Life-Sized Model: A Prospective Case Series.Journal of clinical medicine · 2024Article
- Clinical Workflow Algorithm for Preoperative Planning, Reduction and Stabilization of Complex Acetabular Fractures with the Support of Three-Dimensional Technologies.Journal of clinical medicine · 2024Article
- Robust kinetics estimation from kinematics via direct collocation.Frontiers in bioengineering and biotechnology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, preoperative planning has undergone significant advancements, with a dual focus: improving the accuracy of implant placement and enhancing the prediction of functional outcomes. These breakthroughs have been made possible through the development of advanced processing methods for 3D preoperative images. These methods not only offer novel visualization techniques but can also be seamlessly integrated into computer-aided design models. Additionally, the refinement of motion capture systems has played a pivotal role in this progress. These "markerless" systems are more straightforward to implement and facilitate easier data analysis. Simultaneously, the emergence of machine learning algorithms, utilizing artificial intelligence, has enabled the amalgamation of anatomical and functional data, leading to highly personalized preoperative plans for patients. The shift in preoperative planning from 2D towards 3D, from static to dynamic, is closely linked to technological advances, which will be described in this instructional review. Finally, the concept of 4D planning, encompassing periarticular soft tissues, will be introduced as a forward-looking development in the field of orthopedic surgery.
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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.