ArticleCurrent medical science2021
Artificial Intelligence to Diagnose Tibial Plateau Fractures: An Intelligent Assistant for Orthopedic Physicians.
Article in Current medical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 43 citations in OpenAlex.
- Do ChatGPT and Gemini provide accurate answers to patient questions about glenohumeral arthritis?JSES reviews, reports, and techniques · 2026Article
- ChatGPT in Orthopedic Trauma: Consistency, Accuracy, and Agreement With Textbook and Expert Opinion.Cureus · 2026Article
- Artificial Intelligence in Orthopaedics: Clinical Performance, Limitations, and Translational Readiness-A Review.Journal of clinical medicine · 2026Review
- Minimizing Missed Diagnoses of Tibial Plateau Fractures: The Role of AI in Radiographic Evaluation.The Journal of bone and joint surgery. American volume · 2026Article
- PlaTiF: A pioneering dataset for orthopedic insights in AI-powered diagnosis of tibial plateau fractures.Scientific data · 2026Article
- On Construction of Tibial Plateau Fracture Detection in Different Radiographic Views Using YOLO Models.Diagnostics (Basel, Switzerland) · 2026Article
- Article
- Deep learning diagnosis of adult tibial plateau fractures: multicenter study with external validation.Radiology advances · 2025Article
- Use of Artificial Intelligence on Imaging and Preoperatory Planning of the Knee Joint: A Scoping Review.Medicina (Kaunas, Lithuania) · 2025Article
- Artificial intelligence in fracture detection on radiographs: a literature review.Japanese journal of radiology · 2025Review
- Integrating blockchain technology with artificial intelligence for the diagnosis of tibial plateau fractures.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025Article
- Is there a difference between the incidence of subtypes of tibial plateau fractures between six different level 1, level 2 and level 3 trauma centers in the Netherlands?BMC musculoskeletal disorders · 2025Article
- Dual-Stream Attention-Based Classification Network for Tibial Plateau Fractures via Diffusion Model Augmentation and Segmentation Map Integration.Current medical science · 2025Article
- Integration of Artificial Intelligence for Diagnostic Methods in Musculoskeletal Conditions: A Systematic Review.Cureus · 2025Review
- Diagnostic performance of ChatGPT in tibial plateau fracture in knee X-ray.Emergency radiology · 2025Article
- Swarm learning network for privacy-preserving and collaborative deep learning assisted diagnosis of fracture: a multi-center diagnostic study.Frontiers in medicine · 2025Article
- Application and Prospects of Deep Learning Technology in Fracture Diagnosis.Current medical science · 2024Review
- Application of ChatGPT for Orthopedic Surgeries and Patient Care.Clinics in orthopedic surgery · 2024Review
- Generative Artificial Intelligence Performs at a Second-Year Orthopedic Resident Level.Cureus · 2024Article
- Application of artificial intelligence in trauma orthopedics: Limitation and prospects.World journal of clinical cases · 2023Review
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo explore a new artificial intelligence (AI)-aided method to assist the clinical diagnosis of tibial plateau fractures (TPFs) and further measure its validity and feasibility.
methodsA total of 542 X-rays of TPFs were collected as a reference database. An AI algorithm (RetinaNet) was trained to analyze and detect TPF on the X-rays. The ability of the AI algorithm was determined by indexes such as detection accuracy and time taken for analysis. The algorithm performance was also compared with orthopedic physicians.
resultsThe AI algorithm showed a detection accuracy of 0.91 for the identification of TPF, which was similar to the performance of orthopedic physicians (0.92±0.03). The average time spent for analysis of the AI was 0.56 s, which was 16 times faster than human performance (8.44±3.26 s).
conclusionThe AI algorithm is a valid and efficient method for the clinical diagnosis of TPF. It can be a useful assistant for orthopedic physicians, which largely promotes clinical workflow and further guarantees the health and security of patients.
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Registered trials
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