ReviewEFORT open reviews2020
Artificial intelligence in orthopaedics: false hope or not? A narrative review along the line of Gartner's hype cycle.
Review in EFORT open reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled 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
- [Application and prospect of machine learning in orthopaedic trauma].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2023Pooled it
- 3D printed patient-specific prostate cancer models to guide nerve-sparing robot-assisted radical prostatectomy: a systematic review.Journal of robotic surgery · 2023Pooled it
- Patients With Femoral Neck Fractures Are at Risk for Conversion to Arthroplasty After Internal Fixation: A Machine-learning Algorithm.Clinical orthopaedics and related research · 2022Trial
- Artificial intelligence in surgical decision-making across the perioperative continuum: a scoping review.Frontiers in digital health · 2026Review
- Surgical Management of Isolated Zygomaticomaxillary Complex Fractures: Role of Objective Morphometric Analysis in Decision-Making.Craniomaxillofacial trauma & reconstruction · 2025Review
- Deep Learning Enhances Weightbearing CT Detection of Lisfranc Instability: A FIXUS-AI Ankle Insight 3D Algorithm.Cureus · 2025Article
- Reimagining healthcare education through nurturing AI-driven innovation.BMC medical education · 2025Review
- Review
- Methodology and development of a machine learning probability calculator: Data heterogeneity limits ability to predict recurrence after arthroscopic Bankart repair.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
- A survey of patient acceptability of the use of artificial intelligence in the diagnosis of paediatric fractures: an observational study.Annals of the Royal College of Surgeons of England · 2024Observational
- Artificial intelligence assisted preoperative planning and 3D-printing guiding frame for percutaneous screw reconstruction in periacetabular metastatic cancer patients.Frontiers in bioengineering and biotechnology · 2024Article
- A Scientometric Worldview of Artificial Intelligence in Musculoskeletal Diseases Since the 21st Century.Journal of multidisciplinary healthcare · 2024Review
- How AI May Transform Musculoskeletal Imaging.Radiology · 2024Review
- The state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals.PloS one · 2024Article
- Role of Artificial Intelligence in Surgical Decision-Making: A Comprehensive Review.Galen medical journal · 2024Review
- Artificial Intelligence and Predictive Modeling in Spinal Oncology: A Narrative Review.International journal of spine surgery · 2023Article
- Best practice in digital orthopaedics.EFORT open reviews · 2023Review
- Development and external validation of automated detection, classification, and localization of ankle fractures: inside the black box of a convolutional neural network (CNN).European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2023Article
- Development and internal validation of a clinical prediction model using machine learning algorithms for 90 day and 2 year mortality in femoral neck fracture patients aged 65 years or above.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) in general, and Machine Learning (ML)-based applications in particular, have the potential to change the scope of healthcare, including orthopaedic surgery.The greatest benefit of ML is in its ability to learn from real-world clinical use and experience, and thereby its capability to improve its own performance.Many successful applications are known in orthopaedics, but have yet to be adopted and evaluated for accuracy and efficacy in patients' care and doctors' workflows.The recent hype around AI triggered hope for development of better risk stratification tools to personalize orthopaedics in all subsequent steps of care, from diagnosis to treatment.Computer vision applications for fracture recognition show promising results to support decision-making, overcome bias, process high-volume workloads without fatigue, and hold the promise of even outperforming doctors in certain tasks.In the near future, AI-derived applications are very likely to assist orthopaedic surgeons rather than replace us. 'If the computer takes over the simple stuff, doctors will have more time again to practice the art of medicine'.
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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.